Refactor the code to support hf model module format & support grefcoco dataset

Former-commit-id: f1abb5a3a405d3a61338739b2f47bfee542378db

README.md

@@ -69,6 +69,7 @@
 <p align="center"> <img src="imgs/fig_overview.jpg" width="100%"> </p>
 
 ## News
+- [x] [2023.8.23] Refactor code, and release new model [LISA-13B-llama2-v1](https://huggingface.co/xinlai/LISA-13B-llama2-v1). welcome to check it out!
 - [x] [2023.8.9] Training code is released!
 - [x] [2023.8.4] [Online Demo](http://103.170.5.190:7860/) is released! 
 - [x] [2023.8.4] [*ReasonSeg* Dataset](https://drive.google.com/drive/folders/125mewyg5Ao6tZ3ZdJ-1-E3n04LGVELqy?usp=sharing) and the [LISA-13B-llama2-v0-explanatory](https://huggingface.co/xinlai/LISA-13B-llama2-v0-explanatory) model are released! 
@@ -189,6 +190,23 @@ When training is finished, to get the full model weight:
 cd ./runs/lisa-7b/ckpt_model && python zero_to_fp32.py . ../pytorch_model.bin
 ```
 
+### Merge LoRA Weight
+Merge the LoRA weights of `pytorch_model.bin`, save the resulting model into your desired path in the Hugging Face format:
+```
+CUDA_VISIBLE_DEVICES="" python merge_lora_weights_and_save_hf_model.py \
+  --version="PATH_TO_LLaVA" \
+  --weight="PATH_TO_pytorch_model.bin" \
+  --save_path="PATH_TO_SAVED_MODEL"
+```
+
+For example:
+```
+CUDA_VISIBLE_DEVICES="" python3 merge_lora_weights_and_save_hf_model.py \
+  --version="./LLaVA/LLaVA-Lightning-7B-v1-1" \
+  --weight="lisa-7b/pytorch_model.bin" \
+  --save_path="./LISA-7B"
+```
+
 ### Validation
 ```
 deepspeed --master_port=24999 train_ds.py \
@@ -202,20 +220,23 @@ deepspeed --master_port=24999 train_ds.py \
 
  
 ## Inference 
-To chat with [LISA-13B-llama2-v0](https://huggingface.co/xinlai/LISA-13B-llama2-v0) or [LISA-13B-llama2-v0-explanatory](https://huggingface.co/xinlai/LISA-13B-llama2-v0-explanatory): (Note that LISA-13B-llama2-v0 currently does not support explanatory answers.)
+
+To chat with [LISA-13B-llama2-v1](https://huggingface.co/xinlai/LISA-13B-llama2-v1) or [LISA-13B-llama2-v1-explanatory] (Coming Soon):
+(Note that `chat.py` currently does not support `v0` models (i.e., `LISA-13B-llama2-v0` and `LISA-13B-llama2-v0-explanatory`), please first checkout to the legacy version repo `git checkout 0e26916` to use the `v0` models.)
 ```
-CUDA_VISIBLE_DEVICES=0 python3 chat.py --version='xinlai/LISA-13B-llama2-v0'
-CUDA_VISIBLE_DEVICES=0 python3 chat.py --version='xinlai/LISA-13B-llama2-v0-explanatory'
+CUDA_VISIBLE_DEVICES=0 python chat.py --version='xinlai/LISA-13B-llama2-v1'
+CUDA_VISIBLE_DEVICES=0 python chat.py --version='xinlai/LISA-13B-llama2-v1-explanatory'
 ```
 To use `bf16` or `fp16` data type for inference:
 ```
-CUDA_VISIBLE_DEVICES=0 python3 chat.py --version='xinlai/LISA-13B-llama2-v0' --precision='bf16'
+CUDA_VISIBLE_DEVICES=0 python chat.py --version='xinlai/LISA-13B-llama2-v1' --precision='bf16'
 ```
 To use `8bit` or `4bit` data type for inference (this enables running 13B model on a single 24G or 12G GPU at some cost of generation quality):
 ```
-CUDA_VISIBLE_DEVICES=0 python3 chat.py --version='xinlai/LISA-13B-llama2-v0' --precision='fp16' --load_in_8bit
-CUDA_VISIBLE_DEVICES=0 python3 chat.py --version='xinlai/LISA-13B-llama2-v0' --precision='fp16' --load_in_4bit
+CUDA_VISIBLE_DEVICES=0 python chat.py --version='xinlai/LISA-13B-llama2-v1' --precision='fp16' --load_in_8bit
+CUDA_VISIBLE_DEVICES=0 python chat.py --version='xinlai/LISA-13B-llama2-v1' --precision='fp16' --load_in_4bit
 ```
+Hint: for 13B model, 16-bit inference consumes 30G VRAM with a single GPU, 8-bit inference consumes 16G, and 4-bit inference consumes 9G.
 
 After that, input the text prompt and then the image path. For example，
 ```
@@ -228,6 +249,15 @@ After that, input the text prompt and then the image path. For example，
 The results should be like:
 <p align="center"> <img src="imgs/example1.jpg" width="22%"> <img src="vis_output/example1_masked_img_0.jpg" width="22%"> <img src="imgs/example2.jpg" width="25%"> <img src="vis_output/example2_masked_img_0.jpg" width="25%"> </p>
 
+## Local Deployment
+
+```
+CUDA_VISIBLE_DEVICES=0 python app.py --version='xinlai/LISA-13B-llama2-v1 --load_in_4bit'
+CUDA_VISIBLE_DEVICES=0 python app.py --version='xinlai/LISA-13B-llama2-v1-explanatory --load_in_4bit'
+```
+By default, we use 4-bit quantization. Feel free to delete the `--load_in_4bit` argument for 16-bit inference or replace it with `--load_in_8bit` argument for 8-bit inference.
+
+
 ## Dataset
 In ReasonSeg, we have collected 1218 images (239 train, 200 val, and 779 test). The training and validation sets can be download from <a href="https://drive.google.com/drive/folders/125mewyg5Ao6tZ3ZdJ-1-E3n04LGVELqy?usp=sharing">**this link**</a>. 
 

app.py

@@ -0,0 +1,333 @@
+import argparse
+import os
+import re
+import sys
+
+import bleach
+import cv2
+import gradio as gr
+import numpy as np
+import torch
+import torch.nn.functional as F
+from PIL import Image
+from transformers import AutoTokenizer, BitsAndBytesConfig, CLIPImageProcessor
+
+from model.LISA import LISAForCausalLM
+from model.llava import conversation as conversation_lib
+from model.llava.mm_utils import tokenizer_image_token
+from model.segment_anything.utils.transforms import ResizeLongestSide
+from utils.utils import (DEFAULT_IM_END_TOKEN, DEFAULT_IM_START_TOKEN,
+                         DEFAULT_IMAGE_TOKEN, IMAGE_TOKEN_INDEX)
+
+
+def parse_args(args):
+    parser = argparse.ArgumentParser(description="LISA chat")
+    parser.add_argument("--version", default="xinlai/LISA-13B-llama2-v1")
+    parser.add_argument("--vis_save_path", default="./vis_output", type=str)
+    parser.add_argument(
+        "--precision",
+        default="fp16",
+        type=str,
+        choices=["fp32", "bf16", "fp16"],
+        help="precision for inference",
+    )
+    parser.add_argument("--image_size", default=1024, type=int, help="image size")
+    parser.add_argument("--model_max_length", default=512, type=int)
+    parser.add_argument("--lora_r", default=8, type=int)
+    parser.add_argument(
+        "--vision-tower", default="openai/clip-vit-large-patch14", type=str
+    )
+    parser.add_argument("--local-rank", default=0, type=int, help="node rank")
+    parser.add_argument("--load_in_8bit", action="store_true", default=False)
+    parser.add_argument("--load_in_4bit", action="store_true", default=False)
+    parser.add_argument("--use_mm_start_end", action="store_true", default=True)
+    parser.add_argument(
+        "--conv_type",
+        default="llava_v1",
+        type=str,
+        choices=["llava_v1", "llava_llama_2"],
+    )
+    return parser.parse_args(args)
+
+
+def preprocess(
+    x,
+    pixel_mean=torch.Tensor([123.675, 116.28, 103.53]).view(-1, 1, 1),
+    pixel_std=torch.Tensor([58.395, 57.12, 57.375]).view(-1, 1, 1),
+    img_size=1024,
+) -> torch.Tensor:
+    """Normalize pixel values and pad to a square input."""
+    # Normalize colors
+    x = (x - pixel_mean) / pixel_std
+    # Pad
+    h, w = x.shape[-2:]
+    padh = img_size - h
+    padw = img_size - w
+    x = F.pad(x, (0, padw, 0, padh))
+    return x
+
+
+args = parse_args(sys.argv[1:])
+os.makedirs(args.vis_save_path, exist_ok=True)
+
+# Create model
+tokenizer = AutoTokenizer.from_pretrained(
+    args.version,
+    cache_dir=None,
+    model_max_length=args.model_max_length,
+    padding_side="right",
+    use_fast=False,
+)
+tokenizer.pad_token = tokenizer.unk_token
+args.seg_token_idx = tokenizer("[SEG]", add_special_tokens=False).input_ids[0]
+
+torch_dtype = torch.float32
+if args.precision == "bf16":
+    torch_dtype = torch.bfloat16
+elif args.precision == "fp16":
+    torch_dtype = torch.half
+
+kwargs = {"torch_dtype": torch_dtype}
+if args.load_in_4bit:
+    kwargs.update(
+        {
+            "torch_dtype": torch.half,
+            "device_map": "auto",
+            "load_in_4bit": True,
+            "quantization_config": BitsAndBytesConfig(
+                load_in_4bit=True,
+                bnb_4bit_compute_dtype=torch.float16,
+                bnb_4bit_use_double_quant=True,
+                bnb_4bit_quant_type="nf4",
+                llm_int8_skip_modules=["visual_model"],
+            ),
+        }
+    )
+elif args.load_in_8bit:
+    kwargs.update(
+        {
+            "torch_dtype": torch.half,
+            "device_map": "auto",
+            "quantization_config": BitsAndBytesConfig(
+                llm_int8_skip_modules=["visual_model"],
+                load_in_8bit=True,
+            ),
+        }
+    )
+
+model = LISAForCausalLM.from_pretrained(
+    args.version, low_cpu_mem_usage=True, seg_token_idx=args.seg_token_idx, **kwargs
+)
+
+model.config.eos_token_id = tokenizer.eos_token_id
+model.config.bos_token_id = tokenizer.bos_token_id
+model.config.pad_token_id = tokenizer.pad_token_id
+
+model.get_model().initialize_vision_modules(model.get_model().config)
+vision_tower = model.get_model().get_vision_tower()
+vision_tower.to(dtype=torch_dtype)
+
+if args.precision == "bf16":
+    model = model.bfloat16().cuda()
+elif (
+    args.precision == "fp16" and (not args.load_in_4bit) and (not args.load_in_8bit)
+):
+    vision_tower = model.get_model().get_vision_tower()
+    model.model.vision_tower = None
+    import deepspeed
+
+    model_engine = deepspeed.init_inference(
+        model=model,
+        dtype=torch.half,
+        replace_with_kernel_inject=True,
+        replace_method="auto",
+    )
+    model = model_engine.module
+    model.model.vision_tower = vision_tower.half().cuda()
+elif args.precision == "fp32":
+    model = model.float().cuda()
+
+vision_tower = model.get_model().get_vision_tower()
+vision_tower.to(device=args.local_rank)
+
+clip_image_processor = CLIPImageProcessor.from_pretrained(model.config.vision_tower)
+transform = ResizeLongestSide(args.image_size)
+
+model.eval()
+
+
+# Gradio
+examples = [
+    [
+        "Where can the driver see the car speed in this image? Please output segmentation mask.",
+        "./resources/imgs/example1.jpg",
+    ],
+    [
+        "Can you segment the food that tastes spicy and hot?",
+        "./resources/imgs/example2.jpg",
+    ],
+    [
+        "Assuming you are an autonomous driving robot, what part of the diagram would you manipulate to control the direction of travel? Please output segmentation mask and explain why.",
+        "./resources/imgs/example1.jpg",
+    ],
+    [
+        "What can make the woman stand higher? Please output segmentation mask and explain why.",
+        "./resources/imgs/example3.jpg",
+    ],
+]
+output_labels = ["Segmentation Output"]
+
+title = "LISA: Reasoning Segmentation via Large Language Model"
+
+description = """
+<font size=4>
+This is the online demo of LISA. \n
+If multiple users are using it at the same time, they will enter a queue, which may delay some time. \n
+**Note**: **Different prompts can lead to significantly varied results**. \n
+**Note**: Please try to **standardize** your input text prompts to **avoid ambiguity**, and also pay attention to whether the **punctuations** of the input are correct. \n
+**Note**: Current model is **LISA-13B-llama2-v0-explanatory**, and 4-bit quantization may impair text-generation quality. \n
+**Usage**: <br>
+&ensp;(1) To let LISA **segment something**, input prompt like: "Can you segment xxx in this image?", "What is xxx in this image? Please output segmentation mask."; <br>
+&ensp;(2) To let LISA **output an explanation**, input prompt like: "What is xxx in this image? Please output segmentation mask and explain why."; <br>
+&ensp;(3) To obtain **solely language output**, you can input like what you should do in current multi-modal LLM (e.g., LLaVA). <br>
+Hope you can enjoy our work!
+</font>
+"""
+
+article = """
+<p style='text-align: center'>
+<a href='https://arxiv.org/abs/2308.00692' target='_blank'>
+Preprint Paper
+</a>
+\n
+<p style='text-align: center'>
+<a href='https://github.com/dvlab-research/LISA' target='_blank'>   Github Repo </a></p>
+"""
+
+
+## to be implemented
+def inference(input_str, input_image):
+    ## filter out special chars
+    input_str = bleach.clean(input_str)
+
+    print("input_str: ", input_str, "input_image: ", input_image)
+
+    ## input valid check
+    if not re.match(r"^[A-Za-z ,.!?\'\"]+$", input_str) or len(input_str) < 1:
+        output_str = "[Error] Invalid input: ", input_str
+        # output_image = np.zeros((128, 128, 3))
+        ## error happened
+        output_image = cv2.imread("./resources/error_happened.png")[:, :, ::-1]
+        return output_image, output_str
+
+    # Model Inference
+    conv = conversation_lib.conv_templates[args.conv_type].copy()
+    conv.messages = []
+
+    prompt = input_str
+    prompt = DEFAULT_IMAGE_TOKEN + "\n" + prompt
+    if args.use_mm_start_end:
+        replace_token = (
+            DEFAULT_IM_START_TOKEN + DEFAULT_IMAGE_TOKEN + DEFAULT_IM_END_TOKEN
+        )
+        prompt = prompt.replace(DEFAULT_IMAGE_TOKEN, replace_token)
+
+    conv.append_message(conv.roles[0], prompt)
+    conv.append_message(conv.roles[1], "")
+    prompt = conv.get_prompt()
+
+    image_np = cv2.imread(image_path)
+    image_np = cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB)
+    original_size_list = [image_np.shape[:2]]
+
+    image_clip = (
+        clip_image_processor.preprocess(image_np, return_tensors="pt")[
+            "pixel_values"
+        ][0]
+        .unsqueeze(0)
+        .cuda()
+    )
+    if args.precision == "bf16":
+        image_clip = image_clip.bfloat16()
+    elif args.precision == "fp16":
+        image_clip = image_clip.half()
+    else:
+        image_clip = image_clip.float()
+
+    image = transform.apply_image(image_np)
+    resize_list = [images.shape[:2]]
+
+    image = (
+        preprocess(torch.from_numpy(image).permute(2, 0, 1).contiguous())
+        .unsqueeze(0)
+        .cuda()
+    )
+    if args.precision == "bf16":
+        image = image.bfloat16()
+    elif args.precision == "fp16":
+        image = image.half()
+    else:
+        image = image.float()
+
+
+    input_ids = tokenizer_image_token(prompt, tokenizer, return_tensors="pt")
+    input_ids = input_ids.unsqueeze(0).cuda()
+
+    output_ids, pred_masks = model.evaluate(
+        image_clip,
+        image,
+        input_ids,
+        resize_list,
+        original_size_list,
+        max_new_tokens=512,
+        tokenizer=tokenizer,
+    )
+    output_ids = output_ids[0][output_ids[0] != IMAGE_TOKEN_INDEX]
+
+    text_output = tokenizer.decode(output_ids, skip_special_tokens=False)
+    text_output = text_output.replace("\n", "").replace("  ", " ")
+    text_output = text_output.split("ASSISTANT: ")[-1]
+
+    print("text_output: ", text_output)
+    save_img = None
+    for i, pred_mask in enumerate(pred_masks):
+        if pred_mask.shape[0] == 0:
+            continue
+
+        pred_mask = pred_mask.detach().cpu().numpy()[0]
+        pred_mask = pred_mask > 0
+
+        save_img = image_np.copy()
+        save_img[pred_mask] = (
+            image_np * 0.5
+            + pred_mask[:, :, None].astype(np.uint8) * np.array([255, 0, 0]) * 0.5
+        )[pred_mask]
+
+    output_str = "ASSITANT: " + text_output  # input_str
+    if save_img is not None:
+        output_image = save_img  # input_image
+    else:
+        ## no seg output
+        output_image = cv2.imread("./resources/no_seg_out.png")[:, :, ::-1]
+    return output_image, output_str
+
+
+demo = gr.Interface(
+    inference,
+    inputs=[
+        gr.Textbox(lines=1, placeholder=None, label="Text Instruction"),
+        gr.Image(type="filepath", label="Input Image"),
+    ],
+    outputs=[
+        gr.Image(type="pil", label="Segmentation Output"),
+        gr.Textbox(lines=1, placeholder=None, label="Text Output"),
+    ],
+    title=title,
+    description=description,
+    article=article,
+    examples=examples,
+    allow_flagging="auto",
+)
+
+demo.queue()
+demo.launch()

chat.py

@@ -3,21 +3,22 @@ import os
 import sys
 
 import cv2
-import glob
 import numpy as np
 import torch
 import torch.nn.functional as F
-import transformers
-from transformers import AutoTokenizer, CLIPImageProcessor
+from transformers import AutoTokenizer, BitsAndBytesConfig, CLIPImageProcessor
 
-from model.LISA import LISA
+from model.LISA import LISAForCausalLM
+from model.llava import conversation as conversation_lib
+from model.llava.mm_utils import tokenizer_image_token
 from model.segment_anything.utils.transforms import ResizeLongestSide
-from utils.conversation import get_default_conv_template
+from utils.utils import (DEFAULT_IM_END_TOKEN, DEFAULT_IM_START_TOKEN,
+                         DEFAULT_IMAGE_TOKEN, IMAGE_TOKEN_INDEX)
 
 
 def parse_args(args):
     parser = argparse.ArgumentParser(description="LISA chat")
-    parser.add_argument("--version", default="xinlai/LISA-13B-llama2-v0")
+    parser.add_argument("--version", default="xinlai/LISA-13B-llama2-v1")
     parser.add_argument("--vis_save_path", default="./vis_output", type=str)
     parser.add_argument(
         "--precision",
@@ -26,15 +27,22 @@ def parse_args(args):
         choices=["fp32", "bf16", "fp16"],
         help="precision for inference",
     )
-    parser.add_argument("--image-size", default=1024, type=int, help="image size")
-    parser.add_argument("--model-max-length", default=512, type=int)
-    parser.add_argument("--lora-r", default=-1, type=int)
+    parser.add_argument("--image_size", default=1024, type=int, help="image size")
+    parser.add_argument("--model_max_length", default=512, type=int)
+    parser.add_argument("--lora_r", default=8, type=int)
     parser.add_argument(
         "--vision-tower", default="openai/clip-vit-large-patch14", type=str
     )
     parser.add_argument("--local-rank", default=0, type=int, help="node rank")
     parser.add_argument("--load_in_8bit", action="store_true", default=False)
     parser.add_argument("--load_in_4bit", action="store_true", default=False)
+    parser.add_argument("--use_mm_start_end", action="store_true", default=True)
+    parser.add_argument(
+        "--conv_type",
+        default="llava_v1",
+        type=str,
+        choices=["llava_v1", "llava_llama_2"],
+    )
     return parser.parse_args(args)
 
 
@@ -60,7 +68,7 @@ def main(args):
     os.makedirs(args.vis_save_path, exist_ok=True)
 
     # Create model
-    tokenizer = transformers.AutoTokenizer.from_pretrained(
+    tokenizer = AutoTokenizer.from_pretrained(
         args.version,
         cache_dir=None,
         model_max_length=args.model_max_length,
@@ -68,58 +76,62 @@ def main(args):
         use_fast=False,
     )
     tokenizer.pad_token = tokenizer.unk_token
-    num_added_tokens = tokenizer.add_tokens("[SEG]")
-    ret_token_idx = tokenizer("[SEG]", add_special_tokens=False).input_ids
-    args.seg_token_idx = ret_token_idx[0]
-
-    model = LISA(
-        args.local_rank,
-        args.seg_token_idx,
-        tokenizer,
-        args.version,
-        args.lora_r,
-        args.precision,
-        load_in_8bit=args.load_in_8bit,
-        load_in_4bit=args.load_in_4bit,
-    )
+    args.seg_token_idx = tokenizer("[SEG]", add_special_tokens=False).input_ids[0]
 
-    if os.path.exists(args.version):
-        model_dir = args.version
-    else: # hack for cached pre-trained weights
-        user_name, model_name = args.version.split("/")
-        cache_dir = "{}/.cache/huggingface/hub/models--{}--{}".format(os.environ['HOME'], user_name, model_name)
-        if os.path.exists(cache_dir):
-            model1_dir = glob.glob("{}/snapshots/*/pytorch_model-visual_model.bin".format(cache_dir))
-            model2_dir = glob.glob("{}/snapshots/*/pytorch_model-text_hidden_fcs.bin".format(cache_dir))
-            if len(model1_dir) == 0 or len(model2_dir) == 0:
-                raise ValueError("Pre-trained weights for visual_model or text_hidden_fcs do not exist in {}.".format(
-                    cache_dir
-                ))
-            model1_dir = ["/".join(x.split("/")[:-1]) for x in model1_dir]
-            model2_dir = ["/".join(x.split("/")[:-1]) for x in model2_dir]
-            model_dir = list(set(model1_dir).intersection(set(model2_dir)))
-            if len(model_dir) == 0:
-                raise ValueError("Pre-trained weights for visual_model or text_hidden_fcs do not exist in {}.".format(
-                    cache_dir
-                ))
-            model_dir = model_dir[0]
-        else:
-            raise ValueError("The path {} does not exists.".format(cache_dir))
 
-    weight = {}
-    visual_model_weight = torch.load(
-        os.path.join(model_dir, "pytorch_model-visual_model.bin")
-    )
-    text_hidden_fcs_weight = torch.load(
-        os.path.join(model_dir, "pytorch_model-text_hidden_fcs.bin")
+    torch_dtype = torch.float32
+    if args.precision == "bf16":
+        torch_dtype = torch.bfloat16
+    elif args.precision == "fp16":
+        torch_dtype = torch.half
+
+    kwargs = {"torch_dtype": torch_dtype}
+    if args.load_in_4bit:
+        kwargs.update(
+            {
+                "torch_dtype": torch.half,
+                "device_map": "auto",
+                "load_in_4bit": True,
+                "quantization_config": BitsAndBytesConfig(
+                    load_in_4bit=True,
+                    bnb_4bit_compute_dtype=torch.float16,
+                    bnb_4bit_use_double_quant=True,
+                    bnb_4bit_quant_type="nf4",
+                    llm_int8_skip_modules=["visual_model"],
+                ),
+            }
+        )
+    elif args.load_in_8bit:
+        kwargs.update(
+            {
+                "torch_dtype": torch.half,
+                "device_map": "auto",
+                "quantization_config": BitsAndBytesConfig(
+                    llm_int8_skip_modules=["visual_model"],
+                    load_in_8bit=True,
+                ),
+            }
+        )
+
+    model = LISAForCausalLM.from_pretrained(
+        args.version, low_cpu_mem_usage=True, seg_token_idx=args.seg_token_idx, **kwargs
     )
-    weight.update(visual_model_weight)
-    weight.update(text_hidden_fcs_weight)
-    missing_keys, unexpected_keys = model.load_state_dict(weight, strict=False)
+
+    model.config.eos_token_id = tokenizer.eos_token_id
+    model.config.bos_token_id = tokenizer.bos_token_id
+    model.config.pad_token_id = tokenizer.pad_token_id
+
+    model.get_model().initialize_vision_modules(model.get_model().config)
+    vision_tower = model.get_model().get_vision_tower()
+    vision_tower.to(dtype=torch_dtype)
 
     if args.precision == "bf16":
         model = model.bfloat16().cuda()
-    elif args.precision == "fp16":
+    elif (
+        args.precision == "fp16" and (not args.load_in_4bit) and (not args.load_in_8bit)
+    ):
+        vision_tower = model.get_model().get_vision_tower()
+        model.model.vision_tower = None
         import deepspeed
 
         model_engine = deepspeed.init_inference(
@@ -129,27 +141,29 @@ def main(args):
             replace_method="auto",
         )
         model = model_engine.module
-    else:
+        model.model.vision_tower = vision_tower.half().cuda()
+    elif args.precision == "fp32":
         model = model.float().cuda()
 
-    DEFAULT_IMAGE_TOKEN = "<image>"
-    DEFAULT_IMAGE_PATCH_TOKEN = "<im_patch>"
-    DEFAULT_IM_START_TOKEN = "<im_start>"
-    DEFAULT_IM_END_TOKEN = "<im_end>"
-    image_token_len = 256
+    vision_tower = model.get_model().get_vision_tower()
+    vision_tower.to(device=args.local_rank)
 
-    clip_image_processor = CLIPImageProcessor.from_pretrained(args.vision_tower)
+    clip_image_processor = CLIPImageProcessor.from_pretrained(model.config.vision_tower)
     transform = ResizeLongestSide(args.image_size)
 
+    model.eval()
+
     while True:
-        conv = get_default_conv_template("vicuna").copy()
+        conv = conversation_lib.conv_templates[args.conv_type].copy()
         conv.messages = []
 
         prompt = input("Please input your prompt: ")
-        prompt = DEFAULT_IMAGE_TOKEN + " " + prompt
-        replace_token = DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-        replace_token = DEFAULT_IM_START_TOKEN + replace_token + DEFAULT_IM_END_TOKEN
-        prompt = prompt.replace(DEFAULT_IMAGE_TOKEN, replace_token)
+        prompt = DEFAULT_IMAGE_TOKEN + "\n" + prompt
+        if args.use_mm_start_end:
+            replace_token = (
+                DEFAULT_IM_START_TOKEN + DEFAULT_IMAGE_TOKEN + DEFAULT_IM_END_TOKEN
+            )
+            prompt = prompt.replace(DEFAULT_IMAGE_TOKEN, replace_token)
 
         conv.append_message(conv.roles[0], prompt)
         conv.append_message(conv.roles[1], "")
@@ -160,79 +174,56 @@ def main(args):
             print("File not found in {}".format(image_path))
             continue
 
-        image = cv2.imread(image_path)
-        image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-        original_size_list = [image.shape[:2]]
+        image_np = cv2.imread(image_path)
+        image_np = cv2.cvtColor(image_np, cv2.COLOR_BGR2RGB)
+        original_size_list = [image_np.shape[:2]]
+
+        image_clip = (
+            clip_image_processor.preprocess(image_np, return_tensors="pt")[
+                "pixel_values"
+            ][0]
+            .unsqueeze(0)
+            .cuda()
+        )
         if args.precision == "bf16":
-            images_clip = (
-                clip_image_processor.preprocess(image, return_tensors="pt")[
-                    "pixel_values"
-                ][0]
-                .unsqueeze(0)
-                .cuda()
-                .bfloat16()
-            )
+            image_clip = image_clip.bfloat16()
         elif args.precision == "fp16":
-            images_clip = (
-                clip_image_processor.preprocess(image, return_tensors="pt")[
-                    "pixel_values"
-                ][0]
-                .unsqueeze(0)
-                .cuda()
-                .half()
-            )
+            image_clip = image_clip.half()
         else:
-            images_clip = (
-                clip_image_processor.preprocess(image, return_tensors="pt")[
-                    "pixel_values"
-                ][0]
-                .unsqueeze(0)
-                .cuda()
-                .float()
-            )
-        images = transform.apply_image(image)
-        resize_list = [images.shape[:2]]
+            image_clip = image_clip.float()
+
+        image = transform.apply_image(image_np)
+        resize_list = [image.shape[:2]]
+
+        image = (
+            preprocess(torch.from_numpy(image).permute(2, 0, 1).contiguous())
+            .unsqueeze(0)
+            .cuda()
+        )
         if args.precision == "bf16":
-            images = (
-                preprocess(torch.from_numpy(images).permute(2, 0, 1).contiguous())
-                .unsqueeze(0)
-                .cuda()
-                .bfloat16()
-            )
+            image = image.bfloat16()
         elif args.precision == "fp16":
-            images = (
-                preprocess(torch.from_numpy(images).permute(2, 0, 1).contiguous())
-                .unsqueeze(0)
-                .cuda()
-                .half()
-            )
+            image = image.half()
         else:
-            images = (
-                preprocess(torch.from_numpy(images).permute(2, 0, 1).contiguous())
-                .unsqueeze(0)
-                .cuda()
-                .float()
-            )
+            image = image.float()
+
+        input_ids = tokenizer_image_token(prompt, tokenizer, return_tensors="pt")
+        input_ids = input_ids.unsqueeze(0).cuda()
 
-        input_ids = tokenizer(prompt).input_ids
-        input_ids = torch.LongTensor(input_ids).unsqueeze(0).cuda()
         output_ids, pred_masks = model.evaluate(
-            images_clip,
-            images,
+            image_clip,
+            image,
             input_ids,
             resize_list,
             original_size_list,
             max_new_tokens=512,
             tokenizer=tokenizer,
         )
-        text_output = tokenizer.decode(output_ids[0], skip_special_tokens=False)
-        text_output = (
-            text_output.replace(DEFAULT_IMAGE_PATCH_TOKEN, "")
-            .replace("\n", "")
-            .replace("  ", "")
-        )
+        output_ids = output_ids[0][output_ids[0] != IMAGE_TOKEN_INDEX]
+
+        text_output = tokenizer.decode(output_ids, skip_special_tokens=False)
+        text_output = text_output.replace("\n", "").replace("  ", " ")
 
-        print("text_output: ", text_output)
         for i, pred_mask in enumerate(pred_masks):
             if pred_mask.shape[0] == 0:
                 continue
@@ -249,9 +240,9 @@ def main(args):
             save_path = "{}/{}_masked_img_{}.jpg".format(
                 args.vis_save_path, image_path.split("/")[-1].split(".")[0], i
             )
-            save_img = image.copy()
+            save_img = image_np.copy()
             save_img[pred_mask] = (
-                image * 0.5
+                image_np * 0.5
                 + pred_mask[:, :, None].astype(np.uint8) * np.array([255, 0, 0]) * 0.5
             )[pred_mask]
             save_img = cv2.cvtColor(save_img, cv2.COLOR_RGB2BGR)

merge_lora_weights_and_save_hf_model.py

@@ -0,0 +1,159 @@
+import argparse
+import glob
+import os
+import sys
+
+import cv2
+import numpy as np
+import torch
+import torch.nn.functional as F
+import transformers
+from peft import LoraConfig, get_peft_model
+from transformers import AutoTokenizer
+
+from model.LISA import LISAForCausalLM
+from utils.utils import DEFAULT_IM_END_TOKEN, DEFAULT_IM_START_TOKEN
+
+
+def parse_args(args):
+    parser = argparse.ArgumentParser(
+        description="merge lora weights and save model with hf format"
+    )
+    parser.add_argument(
+        "--version", default="liuhaotian/llava-llama-2-13b-chat-lightning-preview"
+    )
+    parser.add_argument("--vis_save_path", default="./vis_output", type=str)
+    parser.add_argument(
+        "--precision",
+        default="bf16",
+        type=str,
+        choices=["fp32", "bf16", "fp16"],
+        help="precision for inference",
+    )
+    parser.add_argument("--vision_pretrained", default="PATH_TO_SAM_ViT-H", type=str)
+    parser.add_argument("--out_dim", default=256, type=int)
+    parser.add_argument("--image_size", default=1024, type=int, help="image size")
+    parser.add_argument("--model_max_length", default=512, type=int)
+    parser.add_argument(
+        "--vision-tower", default="openai/clip-vit-large-patch14", type=str
+    )
+    parser.add_argument("--lora_r", default=8, type=int)
+    parser.add_argument("--lora_alpha", default=16, type=int)
+    parser.add_argument("--lora_dropout", default=0.05, type=float)
+    parser.add_argument("--lora_target_modules", default="q_proj,v_proj", type=str)
+    parser.add_argument("--local-rank", default=0, type=int, help="node rank")
+    parser.add_argument("--train_mask_decoder", action="store_true", default=True)
+    parser.add_argument("--use_mm_start_end", action="store_true", default=True)
+    parser.add_argument(
+        "--conv_type",
+        default="llava_v1",
+        type=str,
+        choices=["llava_v1", "llava_llama_2"],
+    )
+    parser.add_argument("--weight", default="", type=str, required=True)
+    parser.add_argument("--save_path", default="./lisa_model", type=str, required=True)
+    return parser.parse_args(args)
+
+
+def main(args):
+    args = parse_args(args)
+    os.makedirs(args.vis_save_path, exist_ok=True)
+
+    # Create model
+    tokenizer = transformers.AutoTokenizer.from_pretrained(
+        args.version,
+        cache_dir=None,
+        model_max_length=args.model_max_length,
+        padding_side="right",
+        use_fast=False,
+    )
+    tokenizer.pad_token = tokenizer.unk_token
+    num_added_tokens = tokenizer.add_tokens("[SEG]")
+    args.seg_token_idx = tokenizer("[SEG]", add_special_tokens=False).input_ids[0]
+
+    if args.use_mm_start_end:
+        tokenizer.add_tokens(
+            [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN], special_tokens=True
+        )
+
+    model_args = {
+        "train_mask_decoder": args.train_mask_decoder,
+        "out_dim": args.out_dim,
+        "seg_token_idx": args.seg_token_idx,
+        "vision_tower": args.vision_tower,
+    }
+
+    torch_dtype = torch.float32
+    if args.precision == "bf16":
+        torch_dtype = torch.bfloat16
+    elif args.precision == "fp16":
+        torch_dtype = torch.half
+    model = LISAForCausalLM.from_pretrained(
+        args.version, torch_dtype=torch_dtype, low_cpu_mem_usage=True, **model_args
+    )
+    model.config.eos_token_id = tokenizer.eos_token_id
+    model.config.bos_token_id = tokenizer.bos_token_id
+    model.config.pad_token_id = tokenizer.pad_token_id
+
+    model.get_model().initialize_vision_modules(model.get_model().config)
+    vision_tower = model.get_model().get_vision_tower()
+    vision_tower.to(dtype=torch_dtype)
+    model.get_model().initialize_lisa_modules(model.get_model().config)
+
+    lora_r = args.lora_r
+    if lora_r > 0:
+
+        def find_linear_layers(model, lora_target_modules):
+            cls = torch.nn.Linear
+            lora_module_names = set()
+            for name, module in model.named_modules():
+                if (
+                    isinstance(module, cls)
+                    and all(
+                        [
+                            x not in name
+                            for x in [
+                                "visual_model",
+                                "vision_tower",
+                                "mm_projector",
+                                "text_hidden_fcs",
+                            ]
+                        ]
+                    )
+                    and any([x in name for x in lora_target_modules])
+                ):
+                    lora_module_names.add(name)
+            return sorted(list(lora_module_names))
+
+        lora_alpha = args.lora_alpha
+        lora_dropout = args.lora_dropout
+        lora_target_modules = find_linear_layers(
+            model, args.lora_target_modules.split(",")
+        )
+        lora_config = LoraConfig(
+            r=lora_r,
+            lora_alpha=lora_alpha,
+            target_modules=lora_target_modules,
+            lora_dropout=lora_dropout,
+            bias="none",
+            task_type="CAUSAL_LM",
+        )
+        model = get_peft_model(model, lora_config)
+        model.print_trainable_parameters()
+
+    model.resize_token_embeddings(len(tokenizer))
+
+    state_dict = torch.load(args.weight, map_location="cpu")
+    model.load_state_dict(state_dict, strict=True)
+
+    model = model.merge_and_unload()
+    state_dict = {}
+    for k, v in model.state_dict().items():
+        if "vision_tower" not in k:
+            state_dict[k] = v
+    model.save_pretrained(args.save_path, state_dict=state_dict)
+    tokenizer.save_pretrained(args.save_path)
+
+
+if __name__ == "__main__":
+    main(sys.argv[1:])

model/LISA.py

@@ -3,16 +3,13 @@ from typing import List
 import torch
 import torch.nn as nn
 import torch.nn.functional as F
-from peft import LoraConfig, get_peft_model
 from transformers import BitsAndBytesConfig, CLIPVisionModel
 
-from utils.utils import (
-    DEFAULT_IM_END_TOKEN,
-    DEFAULT_IM_START_TOKEN,
-    DEFAULT_IMAGE_PATCH_TOKEN,
-)
+from utils.utils import (DEFAULT_IM_END_TOKEN, DEFAULT_IM_START_TOKEN,
+                         DEFAULT_IMAGE_PATCH_TOKEN)
 
-from .llava.model.llava import LlavaLlamaForCausalLM
+from .llava.model.language_model.llava_llama import (LlavaLlamaForCausalLM,
+                                                     LlavaLlamaModel)
 from .segment_anything import build_sam_vit_h
 
 
@@ -62,183 +59,36 @@ def sigmoid_ce_loss(
     return loss
 
 
-class LISA(nn.Module):
+class LisaMetaModel:
     def __init__(
         self,
-        local_rank,
-        seg_token_idx,
-        tokenizer,
-        llm_version,
-        lora_r,
-        precision,
-        load_in_4bit=False,
-        load_in_8bit=False,
-        lora_target_modules=["q_proj", "v_proj"],
-        lora_alpha=16,
-        lora_dropout=0.05,
-        vision_tower="openai/clip-vit-large-patch14",
-        mm_vision_select_layer=-2,
-        freeze_lm=True,
-        train_mask_decoder=True,
-        out_dim=256,
-        ce_loss_weight=1.0,
-        dice_loss_weight=0.5,
-        bce_loss_weight=2.0,
-        vision_pretrained=None,
+        config,
+        **kwargs,
     ):
-        super().__init__()
-        self.local_rank = local_rank
-        self.tokenizer = tokenizer
-        self.image_token = tokenizer.cls_token_id
-        self.precision = precision
-        self.ce_loss_weight = ce_loss_weight
-        self.dice_loss_weight = dice_loss_weight
-        self.bce_loss_weight = bce_loss_weight
-
-        # LLaVA
-        tokenizer.add_tokens([DEFAULT_IMAGE_PATCH_TOKEN], special_tokens=True)
-        num_new_tokens = tokenizer.add_tokens(
-            [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN], special_tokens=True
-        )
-        if precision == "bf16":
-            self.lm = LlavaLlamaForCausalLM.from_pretrained(
-                llm_version,
-                torch_dtype=torch.bfloat16,
-                cache_dir=None,
-                low_cpu_mem_usage=True,
-            )
-        elif precision == "fp16":
-            if load_in_4bit:
-                self.lm = LlavaLlamaForCausalLM.from_pretrained(
-                    llm_version,
-                    load_in_4bit=True,
-                    cache_dir=None,
-                    low_cpu_mem_usage=True,
-                    device_map="auto",
-                    quantization_config=BitsAndBytesConfig(
-                        load_in_4bit=True,
-                        bnb_4bit_compute_dtype=torch.float16,
-                        bnb_4bit_use_double_quant=True,
-                        bnb_4bit_quant_type="nf4",
-                    ),
-                )
-            elif load_in_8bit:
-                self.lm = LlavaLlamaForCausalLM.from_pretrained(
-                    llm_version,
-                    load_in_8bit=True,
-                    cache_dir=None,
-                    low_cpu_mem_usage=True,
-                    device_map="auto",
-                )
-            else:
-                self.lm = LlavaLlamaForCausalLM.from_pretrained(
-                    llm_version,
-                    torch_dtype=torch.half,
-                    cache_dir=None,
-                    low_cpu_mem_usage=True,
-                )
-        else:
-            self.lm = LlavaLlamaForCausalLM.from_pretrained(
-                llm_version,
-                torch_dtype=torch.float32,
-                cache_dir=None,
-                low_cpu_mem_usage=True,
-            )
+        super(LisaMetaModel, self).__init__(config)
 
-        self.lm.enable_input_require_grads()
-        self.lm.gradient_checkpointing_enable()
-        self.lm.config.use_cache = False
-        model_vision_dict = self.lm.get_model().initialize_vision_modules(
-            vision_tower=vision_tower,
-            mm_vision_select_layer=mm_vision_select_layer,
-            precision=precision,
-        )
-        vision_config = model_vision_dict["vision_config"]
-        vision_tower = self.lm.get_model().vision_tower[0]
-        self.lm.model.config.eos_token_id = tokenizer.eos_token_id
-        self.lm.model.config.bos_token_id = tokenizer.bos_token_id
-        self.lm.model.config.pad_token_id = tokenizer.pad_token_id
-
-        if vision_tower.device.type == "meta":
-            if precision == "bf16":
-                vision_tower = CLIPVisionModel.from_pretrained(
-                    vision_tower.config._name_or_path,
-                    torch_dtype=torch.bfloat16,
-                    low_cpu_mem_usage=True,
-                ).cuda(local_rank)
-            elif precision == "fp16":
-                vision_tower = CLIPVisionModel.from_pretrained(
-                    vision_tower.config._name_or_path,
-                    torch_dtype=torch.half,
-                    low_cpu_mem_usage=True,
-                ).cuda(local_rank)
-            else:
-                vision_tower = CLIPVisionModel.from_pretrained(
-                    vision_tower.config._name_or_path,
-                    torch_dtype=torch.float32,
-                    low_cpu_mem_usage=True,
-                ).cuda(local_rank)
-            self.lm.get_model().vision_tower[0] = vision_tower
+        self.config = config
+        if not hasattr(self.config, "train_mask_decoder"):
+            self.config.train_mask_decoder = kwargs["train_mask_decoder"]
+            self.config.out_dim = kwargs["out_dim"]
+            self.vision_pretrained = kwargs.get("vision_pretrained", None)
         else:
-            if precision == "bf16":
-                vision_tower.to(device="cuda", dtype=torch.bfloat16)
-            elif precision == "fp16":
-                vision_tower.to(device="cuda", dtype=torch.half)
-            else:
-                vision_tower.to(device="cuda", dtype=torch.float32)
-
-        self.lm.config.tune_mm_mlp_adapter = False
-        self.lm.config.freeze_mm_mlp_adapter = False
-        self.lm.config.mm_use_im_start_end = True
-        vision_config.use_im_start_end = True
-        self.lm.config.sep_image_conv_front = False
-
-        self.lm.initialize_vision_tokenizer(
-            mm_use_im_start_end=True,
-            tokenizer=tokenizer,
-            num_new_tokens=num_new_tokens,
-            device=local_rank,
-            tune_mm_mlp_adapter=False,
-        )
-        if freeze_lm:
-            for n, param in self.lm.named_parameters():
-                param.requires_grad = False
-
-        # LoRA
-        if lora_r > 0:
-            config = LoraConfig(
-                r=lora_r,
-                lora_alpha=lora_alpha,
-                target_modules=lora_target_modules,
-                lora_dropout=lora_dropout,
-                bias="none",
-                task_type="CAUSAL_LM",
-            )
-            self.lm = get_peft_model(self.lm, config)
-            self.lm.print_trainable_parameters()
-
-        self.llm_version = llm_version
-
-        self.seg_token_idx = seg_token_idx
-        self.lm.resize_token_embeddings(len(tokenizer))
-
-        for n, p in self.lm.named_parameters():
-            if any([x in n for x in ["lm_head", "embed_tokens"]]) and p.shape[0] == len(
-                tokenizer
-            ):
-                p.requires_grad = True
+            self.vision_pretrained = kwargs.get("vision_pretrained", None)
+            self.initialize_lisa_modules(self.config)
 
+    def initialize_lisa_modules(self, config):
         # SAM
-        self.visual_model = build_sam_vit_h(vision_pretrained)
+        self.visual_model = build_sam_vit_h(self.vision_pretrained)
         for param in self.visual_model.parameters():
             param.requires_grad = False
-        if train_mask_decoder:
+        if config.train_mask_decoder:
             self.visual_model.mask_decoder.train()
             for param in self.visual_model.mask_decoder.parameters():
                 param.requires_grad = True
 
         # Projection layer
-        in_dim = self.lm.config.hidden_size
+        in_dim = config.hidden_size
+        out_dim = config.out_dim
         text_fc = [
             nn.Linear(in_dim, in_dim),
             nn.ReLU(inplace=True),
@@ -246,13 +96,75 @@ class LISA(nn.Module):
             nn.Dropout(0.0),
         ]
         self.text_hidden_fcs = nn.ModuleList([nn.Sequential(*text_fc)])
+        self.text_hidden_fcs.train()
+        for param in self.text_hidden_fcs.parameters():
+            param.requires_grad = True
+
+
+class LisaModel(LisaMetaModel, LlavaLlamaModel):
+    def __init__(
+        self,
+        config,
+        **kwargs,
+    ):
+        super(LisaModel, self).__init__(config, **kwargs)
+
+        self.config.use_cache = False
+        self.config.vision_tower = self.config.mm_vision_tower
+        self.config.mm_vision_select_feature = "patch"
+        self.config.image_aspect_ratio = "square"
+        self.config.image_grid_pinpoints = None
+        self.config.tune_mm_mlp_adapter = False
+        self.config.freeze_mm_mlp_adapter = True
+        self.config.pretrain_mm_mlp_adapter = None
+        self.config.mm_use_im_patch_token = False
+
+
+class LISAForCausalLM(LlavaLlamaForCausalLM):
+    def __init__(
+        self,
+        config,
+        **kwargs,
+    ):
+        if not hasattr(config, "train_mask_decoder"):
+            config.mm_use_im_start_end = kwargs.pop("use_mm_start_end", True)
+            config.mm_vision_tower = kwargs.get(
+                "vision_tower", "openai/clip-vit-large-patch14"
+            )
+            self.ce_loss_weight = kwargs.pop("ce_loss_weight", None)
+            self.dice_loss_weight = kwargs.pop("dice_loss_weight", None)
+            self.bce_loss_weight = kwargs.pop("bce_loss_weight", None)
+
+        self.seg_token_idx = kwargs.pop("seg_token_idx")
+
+        super().__init__(config)
+
+        self.model = LisaModel(config, **kwargs)
+
+        self.lm_head = nn.Linear(config.hidden_size, config.vocab_size, bias=False)
+
+        # Initialize weights and apply final processing
+        self.post_init()
 
     def get_visual_embs(self, pixel_values: torch.FloatTensor):
         with torch.no_grad():
-            image_embeddings = self.visual_model.image_encoder(pixel_values)
+            image_embeddings_list = []
+            for i in range(pixel_values.shape[0]):
+                torch.cuda.empty_cache()
+                image_embeddings = self.model.visual_model.image_encoder(
+                    pixel_values[i].unsqueeze(0)
+                )
+                image_embeddings_list.append(image_embeddings)
+            torch.cuda.empty_cache()
+            image_embeddings = torch.cat(image_embeddings_list, 0)
         return image_embeddings
 
-    def forward(
+    def forward(self, **kwargs):
+        if "past_key_values" in kwargs:
+            return super().forward(**kwargs)
+        return self.model_forward(**kwargs)
+
+    def model_forward(
         self,
         images: torch.FloatTensor,
         images_clip: torch.FloatTensor,
@@ -274,10 +186,15 @@ class LISA(nn.Module):
         seg_token_mask = torch.cat(
             [
                 seg_token_mask,
-                torch.zeros((seg_token_mask.shape[0], 1)).bool().cuda(self.local_rank),
+                torch.zeros((seg_token_mask.shape[0], 1)).bool().cuda(),
             ],
             dim=1,
         )
+        # hack for IMAGE_TOKEN_INDEX (we suppose that there is only one image, and it is in the front)
+        seg_token_mask = torch.cat(
+            [torch.zeros((seg_token_mask.shape[0], 255)).bool().cuda(), seg_token_mask],
+            dim=1,
+        )
 
         if inference:
             n_batch = 1
@@ -288,7 +205,7 @@ class LISA(nn.Module):
             output_hidden_states = []
             for i in range(n_batch):
                 start_i, end_i = i * length, min((i + 1) * length, input_ids.shape[0])
-                output_i = self.lm(
+                output_i = super().forward(
                     images=images_clip_extend[: end_i - start_i],
                     attention_mask=attention_masks[start_i:end_i],
                     input_ids=input_ids[start_i:end_i],
@@ -316,7 +233,7 @@ class LISA(nn.Module):
                 images_clip_list.append(images_clip_i)
             images_clip = torch.cat(images_clip_list, dim=0)
 
-            output = self.lm(
+            output = super().forward(
                 images=images_clip,
                 attention_mask=attention_masks,
                 input_ids=input_ids,
@@ -327,11 +244,10 @@ class LISA(nn.Module):
 
         hidden_states = []
 
-        assert len(self.text_hidden_fcs) == 1
-        hidden_states.append(self.text_hidden_fcs[0](output_hidden_states[-1]))
+        assert len(self.model.text_hidden_fcs) == 1
+        hidden_states.append(self.model.text_hidden_fcs[0](output_hidden_states[-1]))
 
         last_hidden_state = torch.stack(hidden_states, dim=-1).sum(dim=-1)
-
         pred_embeddings = last_hidden_state[seg_token_mask]
         seg_token_counts = seg_token_mask.int().sum(-1)  # [bs, ]
 
@@ -351,21 +267,24 @@ class LISA(nn.Module):
         multimask_output = False
         pred_masks = []
         for i in range(len(pred_embeddings)):
-            sparse_embeddings, dense_embeddings = self.visual_model.prompt_encoder(
+            (
+                sparse_embeddings,
+                dense_embeddings,
+            ) = self.model.visual_model.prompt_encoder(
                 points=None,
                 boxes=None,
                 masks=None,
                 text_embeds=pred_embeddings[i].unsqueeze(1),
             )
             sparse_embeddings = sparse_embeddings.to(pred_embeddings[i].dtype)
-            low_res_masks, iou_predictions = self.visual_model.mask_decoder(
+            low_res_masks, iou_predictions = self.model.visual_model.mask_decoder(
                 image_embeddings=image_embeddings[i].unsqueeze(0),
-                image_pe=self.visual_model.prompt_encoder.get_dense_pe(),
+                image_pe=self.model.visual_model.prompt_encoder.get_dense_pe(),
                 sparse_prompt_embeddings=sparse_embeddings,
                 dense_prompt_embeddings=dense_embeddings,
                 multimask_output=multimask_output,
             )
-            pred_mask = self.visual_model.postprocess_masks(
+            pred_mask = self.model.visual_model.postprocess_masks(
                 low_res_masks,
                 input_size=resize_list[i],
                 original_size=label_list[i].shape,
@@ -433,7 +352,7 @@ class LISA(nn.Module):
         tokenizer=None,
     ):
         with torch.no_grad():
-            outputs = self.lm.generate(
+            outputs = self.generate(
                 images=images_clip,
                 input_ids=input_ids,
                 max_new_tokens=max_new_tokens,
@@ -445,11 +364,19 @@ class LISA(nn.Module):
             output_ids = outputs.sequences
 
             seg_token_mask = output_ids[:, 1:] == self.seg_token_idx
+            # hack for IMAGE_TOKEN_INDEX (we suppose that there is only one image, and it is in the front)
+            seg_token_mask = torch.cat(
+                [
+                    torch.zeros((seg_token_mask.shape[0], 255)).bool().cuda(),
+                    seg_token_mask,
+                ],
+                dim=1,
+            )
 
             hidden_states = []
 
-            assert len(self.text_hidden_fcs) == 1
-            hidden_states.append(self.text_hidden_fcs[0](output_hidden_states))
+            assert len(self.model.text_hidden_fcs) == 1
+            hidden_states.append(self.model.text_hidden_fcs[0](output_hidden_states))
 
             last_hidden_state = torch.stack(hidden_states, dim=-1).sum(dim=-1)
             pred_embeddings = last_hidden_state[seg_token_mask]
@@ -471,7 +398,10 @@ class LISA(nn.Module):
             multimask_output = False
             pred_masks = []
             for i in range(len(pred_embeddings)):
-                sparse_embeddings, dense_embeddings = self.visual_model.prompt_encoder(
+                (
+                    sparse_embeddings,
+                    dense_embeddings,
+                ) = self.model.visual_model.prompt_encoder(
                     points=None,
                     boxes=None,
                     masks=None,
@@ -479,15 +409,14 @@ class LISA(nn.Module):
                 )
 
                 sparse_embeddings = sparse_embeddings.to(pred_embeddings[i].dtype)
-                low_res_masks, iou_predictions = self.visual_model.mask_decoder(
+                low_res_masks, iou_predictions = self.model.visual_model.mask_decoder(
                     image_embeddings=image_embeddings[i].unsqueeze(0),
-                    image_pe=self.visual_model.prompt_encoder.get_dense_pe(),
+                    image_pe=self.model.visual_model.prompt_encoder.get_dense_pe(),
                     sparse_prompt_embeddings=sparse_embeddings,
                     dense_prompt_embeddings=dense_embeddings,
                     multimask_output=multimask_output,
                 )
-
-                pred_mask = self.visual_model.postprocess_masks(
+                pred_mask = self.model.visual_model.postprocess_masks(
                     low_res_masks,
                     input_size=resize_list[i],
                     original_size=original_size_list[i],

model/llava/constants.py

@@ -2,3 +2,11 @@ CONTROLLER_HEART_BEAT_EXPIRATION = 30
 WORKER_HEART_BEAT_INTERVAL = 15
 
 LOGDIR = "."
+
+# Model Constants
+IGNORE_INDEX = -100
+IMAGE_TOKEN_INDEX = -200
+DEFAULT_IMAGE_TOKEN = "<image>"
+DEFAULT_IMAGE_PATCH_TOKEN = "<im_patch>"
+DEFAULT_IM_START_TOKEN = "<im_start>"
+DEFAULT_IM_END_TOKEN = "<im_end>"

model/llava/conversation.py

@@ -9,6 +9,8 @@ class SeparatorStyle(Enum):
     SINGLE = auto()
     TWO = auto()
     MPT = auto()
+    PLAIN = auto()
+    LLAMA_2 = auto()
 
 
 @dataclasses.dataclass
@@ -27,40 +29,83 @@ class Conversation:
     skip_next: bool = False
 
     def get_prompt(self):
+        messages = self.messages
+        if len(messages) > 0 and type(messages[0][1]) is tuple:
+            messages = self.messages.copy()
+            init_role, init_msg = messages[0].copy()
+            init_msg = init_msg[0].replace("<image>", "").strip()
+            if "mmtag" in self.version:
+                messages[0] = (init_role, init_msg)
+                messages.insert(0, (self.roles[0], "<Image><image></Image>"))
+                messages.insert(1, (self.roles[1], "Received."))
+            else:
+                messages[0] = (init_role, "<image>\n" + init_msg)
+
         if self.sep_style == SeparatorStyle.SINGLE:
             ret = self.system + self.sep
-            for role, message in self.messages:
+            for role, message in messages:
                 if message:
                     if type(message) is tuple:
                         message, _, _ = message
                     ret += role + ": " + message + self.sep
                 else:
                     ret += role + ":"
-            return ret
         elif self.sep_style == SeparatorStyle.TWO:
             seps = [self.sep, self.sep2]
             ret = self.system + seps[0]
-            for i, (role, message) in enumerate(self.messages):
+            for i, (role, message) in enumerate(messages):
                 if message:
                     if type(message) is tuple:
                         message, _, _ = message
                     ret += role + ": " + message + seps[i % 2]
                 else:
                     ret += role + ":"
-            return ret
-        if self.sep_style == SeparatorStyle.MPT:
+        elif self.sep_style == SeparatorStyle.MPT:
             ret = self.system + self.sep
-            for role, message in self.messages:
+            for role, message in messages:
                 if message:
                     if type(message) is tuple:
                         message, _, _ = message
                     ret += role + message + self.sep
                 else:
                     ret += role
-            return ret
+        elif self.sep_style == SeparatorStyle.LLAMA_2:
+            wrap_sys = lambda msg: f"<<SYS>>\n{msg}\n<</SYS>>\n\n"
+            wrap_inst = lambda msg: f"[INST] {msg} [/INST]"
+            ret = ""
+
+            for i, (role, message) in enumerate(messages):
+                if i == 0:
+                    assert message, "first message should not be none"
+                    assert role == self.roles[0], "first message should come from user"
+                if message:
+                    if type(message) is tuple:
+                        message, _, _ = message
+                    if i == 0:
+                        message = wrap_sys(self.system) + message
+                    if i % 2 == 0:
+                        message = wrap_inst(message)
+                        ret += self.sep + message
+                    else:
+                        ret += " " + message + " " + self.sep2
+                else:
+                    ret += ""
+            ret = ret.lstrip(self.sep)
+        elif self.sep_style == SeparatorStyle.PLAIN:
+            seps = [self.sep, self.sep2]
+            ret = self.system
+            for i, (role, message) in enumerate(messages):
+                if message:
+                    if type(message) is tuple:
+                        message, _, _ = message
+                    ret += message + seps[i % 2]
+                else:
+                    ret += ""
         else:
             raise ValueError(f"Invalid style: {self.sep_style}")
 
+        return ret
+
     def append_message(self, role, message):
         self.messages.append([role, message])
 
@@ -98,7 +143,7 @@ class Conversation:
                     elif image_process_mode == "Crop":
                         pass
                     elif image_process_mode == "Resize":
-                        image = image.resize((224, 224))
+                        image = image.resize((336, 336))
                     else:
                         raise ValueError(
                             f"Invalid image_process_mode: {image_process_mode}"
@@ -118,7 +163,7 @@ class Conversation:
                         images.append(image)
                     else:
                         buffered = BytesIO()
-                        image.save(buffered, format="JPEG")
+                        image.save(buffered, format="PNG")
                         img_b64_str = base64.b64encode(buffered.getvalue()).decode()
                         images.append(img_b64_str)
         return images
@@ -143,13 +188,16 @@ class Conversation:
                     else:
                         H, W = shortest_edge, longest_edge
                     image = image.resize((W, H))
-                    # image = image.resize((224, 224))
                     buffered = BytesIO()
                     image.save(buffered, format="JPEG")
                     img_b64_str = base64.b64encode(buffered.getvalue()).decode()
                     img_str = f'<img src="data:image/png;base64,{img_b64_str}" alt="user upload image" />'
-                    msg = msg.replace("<image>", img_str)
-                ret.append([msg, None])
+                    ret.append([img_str, None])
+                    msg = msg.replace("<image>", "").strip()
+                    if len(msg) > 0:
+                        ret.append([msg, None])
+                else:
+                    ret.append([msg, None])
             else:
                 ret[-1][-1] = msg
         return ret
@@ -163,6 +211,7 @@ class Conversation:
             sep_style=self.sep_style,
             sep=self.sep,
             sep2=self.sep2,
+            version=self.version,
         )
 
     def dict(self):
@@ -187,36 +236,7 @@ class Conversation:
         }
 
 
-conv_v1 = Conversation(
-    system="A chat between a curious human and an artificial intelligence assistant. "
-    "The assistant gives helpful, detailed, and polite answers to the human's questions.",
-    roles=("Human", "Assistant"),
-    messages=(
-        ("Human", "Give three tips for staying healthy."),
-        (
-            "Assistant",
-            "Sure, here are three tips for staying healthy:\n"
-            "1. Exercise regularly: Regular physical activity can help improve your overall health and wellbeing. "
-            "It can also help reduce your risk of chronic conditions such as obesity, diabetes, heart disease, "
-            "and certain cancers. Aim for at least 150 minutes of moderate-intensity aerobic exercise or "
-            "75 minutes of vigorous-intensity aerobic exercise per week, along with muscle-strengthening "
-            "activities at least two days per week.\n"
-            "2. Eat a balanced diet: Eating a balanced diet that is rich in fruits, "
-            "vegetables, whole grains, lean proteins, and healthy fats can help support "
-            "your overall health. Try to limit your intake of processed and high-sugar foods, "
-            "and aim to drink plenty of water throughout the day.\n"
-            "3. Get enough sleep: Getting enough quality sleep is essential for your physical "
-            "and mental health. Adults should aim for seven to nine hours of sleep per night. "
-            "Establish a regular sleep schedule and try to create a relaxing bedtime routine to "
-            "help improve the quality of your sleep.",
-        ),
-    ),
-    offset=2,
-    sep_style=SeparatorStyle.SINGLE,
-    sep="###",
-)
-
-conv_v1_2 = Conversation(
+conv_vicuna_v0 = Conversation(
     system="A chat between a curious human and an artificial intelligence assistant. "
     "The assistant gives helpful, detailed, and polite answers to the human's questions.",
     roles=("Human", "Assistant"),
@@ -252,7 +272,7 @@ conv_v1_2 = Conversation(
     sep="###",
 )
 
-conv_vicuna_v1_1 = Conversation(
+conv_vicuna_v1 = Conversation(
     system="A chat between a curious user and an artificial intelligence assistant. "
     "The assistant gives helpful, detailed, and polite answers to the user's questions.",
     roles=("USER", "ASSISTANT"),
@@ -264,25 +284,35 @@ conv_vicuna_v1_1 = Conversation(
     sep2="</s>",
 )
 
-conv_mpt = Conversation(
-    system="""<|im_start|>system
-- You are a helpful language and vision assistant.
-- You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.
-- You should follow the instructions carefully and explain your answers in detail.""",
-    roles=("<|im_start|>user\n", "<|im_start|>assistant\n"),
-    version="mpt",
+conv_llama_2 = Conversation(
+    system="""You are a helpful, respectful and honest assistant. Always answer as helpfully as possible, while being safe.  Your answers should not include any harmful, unethical, racist, sexist, toxic, dangerous, or illegal content. Please ensure that your responses are socially unbiased and positive in nature.
+
+If a question does not make any sense, or is not factually coherent, explain why instead of answering something not correct. If you don't know the answer to a question, please don't share false information.""",
+    roles=("USER", "ASSISTANT"),
+    version="llama_v2",
     messages=(),
     offset=0,
-    sep_style=SeparatorStyle.MPT,
-    sep="<|im_end|>",
+    sep_style=SeparatorStyle.LLAMA_2,
+    sep="<s>",
+    sep2="</s>",
 )
 
-conv_mpt_text = Conversation(
+conv_llava_llama_2 = Conversation(
+    system="You are a helpful language and vision assistant. "
+    "You are able to understand the visual content that the user provides, "
+    "and assist the user with a variety of tasks using natural language.",
+    roles=("USER", "ASSISTANT"),
+    version="llama_v2",
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.LLAMA_2,
+    sep="<s>",
+    sep2="</s>",
+)
+
+conv_mpt = Conversation(
     system="""<|im_start|>system
-- You are a helpful assistant chatbot trained by MosaicML.
-- You answer questions.
-- You are excited to be able to help the user, but will refuse to do anything that could be considered harmful to the user.
-- You are more than just an information source, you are also able to write poetry, short stories, and make jokes.""",
+A conversation between a user and an LLM-based AI assistant. The assistant gives helpful and honest answers.""",
     roles=("<|im_start|>user\n", "<|im_start|>assistant\n"),
     version="mpt",
     messages=(),
@@ -291,75 +321,40 @@ conv_mpt_text = Conversation(
     sep="<|im_end|>",
 )
 
-conv_bair_v1 = Conversation(
-    system="BEGINNING OF CONVERSATION:",
-    roles=("USER", "GPT"),
+conv_llava_plain = Conversation(
+    system="",
+    roles=("", ""),
     messages=(),
     offset=0,
-    sep_style=SeparatorStyle.TWO,
-    sep=" ",
-    sep2="</s>",
+    sep_style=SeparatorStyle.PLAIN,
+    sep="\n",
 )
 
-simple_conv = Conversation(
-    system="You are LLaVA, a large language model trained by UW Madison WAIV Lab, based on LLaMA architecture."
-    "You are designed to assist human with a variety of tasks using natural language."
-    "Follow the instructions carefully.",
+conv_llava_v0 = Conversation(
+    system="A chat between a curious human and an artificial intelligence assistant. "
+    "The assistant gives helpful, detailed, and polite answers to the human's questions.",
     roles=("Human", "Assistant"),
-    messages=(
-        ("Human", "Hi!"),
-        ("Assistant", "Hi there!  How can I help you today?\n"),
-    ),
+    messages=(("Human", "Hi!"), ("Assistant", "Hi there! How can I help you today?")),
     offset=2,
     sep_style=SeparatorStyle.SINGLE,
     sep="###",
 )
 
-simple_conv_multimodal = Conversation(
-    system="You are LLaVA, a large language and vision assistant trained by UW Madison WAIV Lab."
-    "You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language."
-    "Follow the instructions carefully and explain your answers in detail.",
+conv_llava_v0_mmtag = Conversation(
+    system="A chat between a curious user and an artificial intelligence assistant. "
+    "The assistant is able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language."
+    "The visual content will be provided with the following format: <Image>visual content</Image>.",
     roles=("Human", "Assistant"),
-    messages=(
-        ("Human", "Hi!"),
-        ("Assistant", "Hi there!  How can I help you today?\n"),
-    ),
-    offset=2,
-    sep_style=SeparatorStyle.SINGLE,
-    sep="###",
-)
-
-simple_conv_mpt_multimodal = Conversation(
-    system="""<|im_start|>system
-- You are LLaVA, a large language and vision assistant trained by UW Madison WAIV Lab.
-- You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language.
-- You should follow the instructions carefully and explain your answers in detail.""",
-    roles=("<|im_start|>user\n", "<|im_start|>assistant\n"),
-    version="mpt",
     messages=(),
     offset=0,
-    sep_style=SeparatorStyle.MPT,
-    sep="<|im_end|>",
-)
-
-simple_conv_legacy = Conversation(
-    system="You are LLaVA, a large language model trained by UW Madison WAIV Lab."
-    "You are designed to assist human with a variety of tasks using natural language."
-    "Follow the instructions carefully.",
-    roles=("Human", "Assistant"),
-    messages=(
-        ("Human", "Hi!\n\n### Response:"),
-        ("Assistant", "Hi there!  How can I help you today?\n"),
-    ),
-    offset=2,
     sep_style=SeparatorStyle.SINGLE,
     sep="###",
+    version="v0_mmtag",
 )
 
 conv_llava_v1 = Conversation(
-    system="You are LLaVA, a large language and vision assistant trained by UW Madison WAIV Lab."
-    "You are able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language."
-    "Follow the instructions carefully and explain your answers in detail.",
+    system="A chat between a curious human and an artificial intelligence assistant. "
+    "The assistant gives helpful, detailed, and polite answers to the human's questions.",
     roles=("USER", "ASSISTANT"),
     version="v1",
     messages=(),
@@ -369,20 +364,34 @@ conv_llava_v1 = Conversation(
     sep2="</s>",
 )
 
-default_conversation = conv_v1_2
+conv_llava_v1_mmtag = Conversation(
+    system="A chat between a curious user and an artificial intelligence assistant. "
+    "The assistant is able to understand the visual content that the user provides, and assist the user with a variety of tasks using natural language."
+    "The visual content will be provided with the following format: <Image>visual content</Image>.",
+    roles=("USER", "ASSISTANT"),
+    messages=(),
+    offset=0,
+    sep_style=SeparatorStyle.TWO,
+    sep=" ",
+    sep2="</s>",
+    version="v1_mmtag",
+)
+
+default_conversation = conv_vicuna_v0
 conv_templates = {
-    "default": conv_v1_2,
-    "simple": simple_conv,
-    "simple_legacy": simple_conv_legacy,
-    "multimodal": simple_conv_multimodal,
-    "mpt_multimodal": simple_conv_mpt_multimodal,
+    "default": conv_vicuna_v0,
+    "v0": conv_vicuna_v0,
+    "v1": conv_vicuna_v1,
+    "vicuna_v1": conv_vicuna_v1,
+    "llama_2": conv_llama_2,
+    "plain": conv_llava_plain,
+    "v0_plain": conv_llava_plain,
+    "llava_v0": conv_llava_v0,
+    "v0_mmtag": conv_llava_v0_mmtag,
     "llava_v1": conv_llava_v1,
-    # fastchat
-    "v1": conv_v1_2,
-    "bair_v1": conv_bair_v1,
-    "vicuna_v1_1": conv_vicuna_v1_1,
+    "v1_mmtag": conv_llava_v1_mmtag,
+    "llava_llama_2": conv_llava_llama_2,
     "mpt": conv_mpt,
-    "mpt_text": conv_mpt_text,
 }
 
 

model/llava/eval/README.md

@@ -1,178 +0,0 @@
-# Evaluations
-
-This directory contains end-to-end pipelines for AI-enhanced evaluation. We will introduce the evaluation pipeline and the data format in this document.
-
-## Generate Answers
-
-### ChatGPT (gpt-3.5-turbo)
-
-Make sure you have setup the OpenAI API Key in your environment. Then run:
-
-```bash
-python qa_baseline_gpt35.py --question table/question.jsonl --output table/answer/answer_gpt35.jsonl
-```
-
-### Bard
-
-Unfortunately, Bard has not release its public APIs till now. You may have to enter the anwsers manually. Or you could find a third-party project that interfaces with Bard.
-
-### Vicuna and others
-
-To generate answers with Vicuna or other models, specify path to the model checkpoint. Then run:
-```bash
-python model_qa.py --model-name /model/path --question-file tables/question.jsonl --answer-file table/answer/answer.jsonl
-```
-
-## Evaluate Answers Automatically
-
-### Generete Reviews with GPT-4
-
-PS: If you do not current have access to GPT-4 API, but you have access to GPT-4 chatbot, you can evaluate the answers manually, according to the instructions in the **Data Format** section. `table/review/*.jsonl` are some examples of reviews.
-
-TODO: add instructions
-
-## Visualize Results
-
-You can generate the data for the webpage by running:
-
-```bash
-python eval/generate_webpage_data_from_table.py
-```
-
-Then you can serve a static website in `webpage` to see the results.
-
-## Data Format
-
-If you want to have a deeper understanding of our evaluation pipeline or want to contribute to the evaluation process, you need to learn the data format we used for evaluation.
-
-Our evaluation data are encoded with [JSON Lines](https://jsonlines.org/).
-
-### Random ID Generation
-
-We use the `shortuuid` Python library for generating short random UUIDs.
-
-```python
-import shortuuid
-shortuuid.uuid() -> str
-```
-
-### Models
-
-`model.jsonl` contains model information we used for generating anwsers.
-
-Each row contains a record of a model with the following field:
-
-* `model_id` (str): A unique ID for a model. Models with different IDs is supposed to have different performance. This ID is generated by `{model_name}:{model_version}`.
-* `model_name` (str): The name of a model. This is not unique, because a model could be trained and updated continuously, but it is still considered as the same model with different versions.
-* `model_version` (str): The version of a model.
-* `model_metadata` (Any): Any metadata of a model (descriptions etc). This is optional.
-
-For example:
-
-```json
-{
-  "model_id": "vicuna-13b:v1",
-  "model_name": "vicuna-13b",
-  "model_version": "v1",
-  "model_metadata": "learning rate 1e-5, 3 epochs, 13b"
-}
-```
-
-### Prompts
-
-We store prompts in `prompt.jsonl`. Each row contains a record of a prompt with the following field:
-
-* `prompt_id` (int): A unique integer ID for a prompt. Prompts with different IDs are supposed to have different purpose.
-* `system_prompt` (str): The system prompt given to a model. This is the prompt that the model sees first.
-* `prompt_template` (str): The prompt body. This is the user prompt that the model sees after the system prompt. It is a Python f-string template, so that we can fill in the inputs later.
-* `defaults` (dict): A dictionary of default values for the prompt template. It can be empty.
-* `description` (str): A description of the functionality of the prompt.
-
-For example:
-
-```json
-{
-  "prompt_id": 1,
-  "system_prompt": "You are a helpful assistant.",
-  "prompt_template": "[Question]\n{question}\n\n[Assistant 1]\n{answer_1}\n\n[End of Assistant 1]\n\n[Assistant 2]\n{answer_2}\n\n[End of Assistant 2]\n\n[System]\n{prompt}\n\n",
-  "defaults": {"prompt": "Which assistant is more helpful?"},
-  "description": "Compare two assistants' answers to a question."
-}
-```
-
-### Reviewers
-
-`reviewer.jsonl` contains reviewer information we used for reviewing answers generated by different models. Each row contains a record of a reviewer with the following field:
-
-* `reviewer_id` (str): A unique ID for a reviewer. Reviewers with different IDs is supposed to have different reviewing performance.
-* `prompt_id` (str): The ID of the prompt given to the reviewer (e.g., an AI assistant). Different prompts could result in different reviewing performance.
-* `metadata` (dict): Metadata of a reviewer about its configurations.
-* `description` (str): A description of the reviewer.
-
-For example:
-
-```json
-{
-  "reviewer_id": "gpt-4-0328-default",
-  "prompt_id": 1,
-  "temperature": 0.2,
-  "max_tokens": 8192,
-  "description": "GPT-4 for generic questions."
-}
-```
-
-### Questions
-
-`question.jsonl` contains questions we used for evaluation. Each row contains a record of a question with the following field:
-
-* `question_id` (int): A unique integer for a question. Questions with different IDs is supposed to be different.
-* `text` (str): The question text.
-* `category` (str): The category of the question. Questions with the same category are supposed to be similar or originate from the same source.
-
-### Answers
-
-`answer/xxx.jsonl` contains answers generated by different models. Each row contains a record of an answer with the following field:
-
-* `answer_id` (str): A unique UUID for an answer. Answers with different IDs is supposed to be different.
-* `question_id` (int): The ID of the question the answer is generated for.
-* `model_id` (str): The ID of the model the answer is generated by.
-* `text` (str): The answer text.
-* `metadata` (dict): Any metadata of the answer.
-
-Example:
-
-```json
-{
-  "answer_id": "[short uuid]",
-  "question_id": 1,
-  "model_id": "vicuna-13b:v1",
-  "text": "Here are five tips...",
-  "metadata": {}
-}
-```
-
-### Reviews
-
-`review/xxx.jsonl` contains reviews given by reviewers, comparing peformance between a pair of models. Each row contains a record of a review with the following field:
-
-* `review_id` (str): A unique UUID for a review. Reviews with different IDs is supposed to be different.
-* `question_id` (int): The ID of the question the review is given for.
-* `answer1_id` (str): The ID of the first answer.
-* `answer2_id` (str): The ID of the second answer.
-* `text` (str): The review text.
-* `score` (list): A list of scores given by the reviewer. The first score is for the first answer, and the second score is for the second answer.
-* `reviewer_id` (str): The ID of the reviewer.
-* `metadata` (dict): Any metadata of the review.
-
-```json
-{
-  "review_id": "[short uuid]",
-  "question_id": 1,
-  "answer1_id": "[answer1_id]",
-  "answer2_id": "[answer2_id]",
-  "text": "Assistant 2 is better...",
-  "score": [9.0, 7.5],
-  "reviewer_id": "gpt-4-0328-default",
-  "metadata": {}
-}
-```

model/llava/eval/eval_gpt_review.py

@@ -1,125 +0,0 @@
-import argparse
-import json
-import os
-import time
-
-import openai
-import ray
-import tqdm
-
-
-@ray.remote(num_cpus=4)
-def get_eval(content: str, max_tokens: int):
-    while True:
-        try:
-            response = openai.ChatCompletion.create(
-                model="gpt-4",
-                messages=[
-                    {
-                        "role": "system",
-                        "content": "You are a helpful and precise assistant for checking the quality of the answer.",
-                    },
-                    {
-                        "role": "user",
-                        "content": content,
-                    },
-                ],
-                temperature=0.2,  # TODO: figure out which temperature is best for evaluation
-                max_tokens=max_tokens,
-            )
-            break
-        except openai.error.RateLimitError:
-            pass
-        except Exception as e:
-            print(e)
-        time.sleep(1)
-
-    print("success!")
-    return response["choices"][0]["message"]["content"]
-
-
-def parse_score(review):
-    try:
-        score_pair = review.split("\n")[0]
-        score_pair = score_pair.replace(",", " ")
-        sp = score_pair.split(" ")
-        if len(sp) == 2:
-            return [float(sp[0]), float(sp[1])]
-        else:
-            print("error", review)
-            return [-1, -1]
-    except Exception as e:
-        print(e)
-        print("error", review)
-        return [-1, -1]
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="ChatGPT-based QA evaluation.")
-    parser.add_argument("-q", "--question")
-    # parser.add_argument('-a', '--answer')
-    parser.add_argument("-a", "--answer-list", nargs="+", default=[])
-    parser.add_argument("-r", "--rule")
-    parser.add_argument("-o", "--output")
-    parser.add_argument(
-        "--max-tokens",
-        type=int,
-        default=1024,
-        help="maximum number of tokens produced in the output",
-    )
-    args = parser.parse_args()
-
-    ray.init()
-
-    f_q = open(os.path.expanduser(args.question))
-    f_ans1 = open(os.path.expanduser(args.answer_list[0]))
-    f_ans2 = open(os.path.expanduser(args.answer_list[1]))
-    rule_dict = json.load(open(os.path.expanduser(args.rule), "r"))
-
-    review_file = open(f"{args.output}", "w")
-
-    js_list = []
-    handles = []
-    idx = 0
-    for ques_js, ans1_js, ans2_js in zip(f_q, f_ans1, f_ans2):
-        # if idx == 1:
-        #     break
-
-        ques = json.loads(ques_js)
-        ans1 = json.loads(ans1_js)
-        ans2 = json.loads(ans2_js)
-
-        category = json.loads(ques_js)["category"]
-        if category in rule_dict:
-            rule = rule_dict[category]
-        else:
-            rule = rule_dict["default"]
-        prompt = rule["prompt"]
-        role = rule["role"]
-        content = (
-            f'[Question]\n{ques["text"]}\n\n'
-            f'[{role} 1]\n{ans1["text"]}\n\n[End of {role} 1]\n\n'
-            f'[{role} 2]\n{ans2["text"]}\n\n[End of {role} 2]\n\n'
-            f"[System]\n{prompt}\n\n"
-        )
-        js_list.append(
-            {
-                "id": idx + 1,
-                "question_id": ques["question_id"],
-                "answer1_id": ans1["answer_id"],
-                "answer2_id": ans2["answer_id"],
-                "category": category,
-            }
-        )
-        idx += 1
-        handles.append(get_eval.remote(content, args.max_tokens))
-        # To avoid the rate limit set by OpenAI
-        time.sleep(1)
-
-    reviews = ray.get(handles)
-    for idx, review in enumerate(reviews):
-        scores = parse_score(review)
-        js_list[idx]["content"] = review
-        js_list[idx]["tuple"] = scores
-        review_file.write(json.dumps(js_list[idx]) + "\n")
-    review_file.close()

model/llava/eval/eval_gpt_review_visual.py

@@ -1,135 +0,0 @@
-import argparse
-import json
-import os
-import time
-
-import openai
-import ray
-import tqdm
-
-
-@ray.remote(num_cpus=4)
-def get_eval(content: str, max_tokens: int):
-    while True:
-        try:
-            response = openai.ChatCompletion.create(
-                model="gpt-4",
-                messages=[
-                    {
-                        "role": "system",
-                        "content": "You are a helpful and precise assistant for checking the quality of the answer.",
-                    },
-                    {
-                        "role": "user",
-                        "content": content,
-                    },
-                ],
-                temperature=0.2,  # TODO: figure out which temperature is best for evaluation
-                max_tokens=max_tokens,
-            )
-            break
-        except openai.error.RateLimitError:
-            pass
-        except Exception as e:
-            print(e)
-        time.sleep(1)
-
-    print("success!")
-    return response["choices"][0]["message"]["content"]
-
-
-def parse_score(review):
-    try:
-        score_pair = review.split("\n")[0]
-        score_pair = score_pair.replace(",", " ")
-        sp = score_pair.split(" ")
-        if len(sp) == 2:
-            return [float(sp[0]), float(sp[1])]
-        else:
-            print("error", review)
-            return [-1, -1]
-    except Exception as e:
-        print(e)
-        print("error", review)
-        return [-1, -1]
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="ChatGPT-based QA evaluation.")
-    parser.add_argument("-q", "--question")
-    parser.add_argument("-c", "--context")
-    parser.add_argument("-a", "--answer-list", nargs="+", default=[])
-    parser.add_argument("-r", "--rule")
-    parser.add_argument("-o", "--output")
-    parser.add_argument(
-        "--max-tokens",
-        type=int,
-        default=1024,
-        help="maximum number of tokens produced in the output",
-    )
-    args = parser.parse_args()
-
-    ray.init()
-
-    f_q = open(os.path.expanduser(args.question))
-    f_ans1 = open(os.path.expanduser(args.answer_list[0]))
-    f_ans2 = open(os.path.expanduser(args.answer_list[1]))
-    rule_dict = json.load(open(os.path.expanduser(args.rule), "r"))
-
-    review_file = open(f"{args.output}", "w")
-
-    context_list = [json.loads(line) for line in open(os.path.expanduser(args.context))]
-    image_to_context = {context["image"]: context for context in context_list}
-
-    js_list = []
-    handles = []
-    idx = 0
-    for ques_js, ans1_js, ans2_js in zip(f_q, f_ans1, f_ans2):
-        ques = json.loads(ques_js)
-        ans1 = json.loads(ans1_js)
-        ans2 = json.loads(ans2_js)
-
-        inst = image_to_context[ques["image"]]
-        cap_str = "\n".join(inst["captions"])
-        box_str = "\n".join(
-            [
-                f'{instance["category"]}: {instance["bbox"]}'
-                for instance in inst["instances"]
-            ]
-        )
-
-        category = json.loads(ques_js)["category"]
-        if category in rule_dict:
-            rule = rule_dict[category]
-        else:
-            assert False, f"Visual QA category not found in rule file: {category}."
-        prompt = rule["prompt"]
-        role = rule["role"]
-        content = (
-            f"[Context]\n{cap_str}\n\n{box_str}\n\n"
-            f'[Question]\n{ques["text"]}\n\n'
-            f'[{role} 1]\n{ans1["text"]}\n\n[End of {role} 1]\n\n'
-            f'[{role} 2]\n{ans2["text"]}\n\n[End of {role} 2]\n\n'
-            f"[System]\n{prompt}\n\n"
-        )
-        js_list.append(
-            {
-                "id": idx + 1,
-                "question_id": ques["question_id"],
-                "answer1_id": ans1.get("answer_id", ans1["question_id"]),
-                "answer2_id": ans2.get("answer_id", ans2["answer_id"]),
-                "category": category,
-            }
-        )
-        idx += 1
-        handles.append(get_eval.remote(content, args.max_tokens))
-        # To avoid the rate limit set by OpenAI
-        time.sleep(1)
-
-    reviews = ray.get(handles)
-    for idx, review in enumerate(reviews):
-        scores = parse_score(review)
-        js_list[idx]["content"] = review
-        js_list[idx]["tuple"] = scores
-        review_file.write(json.dumps(js_list[idx]) + "\n")
-    review_file.close()

model/llava/eval/eval_science_qa.py

@@ -1,103 +0,0 @@
-import argparse
-import json
-import os
-import random
-import re
-
-
-def get_args():
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--base-dir", type=str)
-    parser.add_argument("--result-file", type=str)
-    parser.add_argument("--output-file", type=str)
-    parser.add_argument("--output-result", type=str)
-    parser.add_argument("--split", type=str, default="test")
-    parser.add_argument("--options", type=list, default=["A", "B", "C", "D", "E"])
-    return parser.parse_args()
-
-
-def convert_caps(results):
-    fakecaps = []
-    for result in results:
-        image_id = result["question_id"]
-        caption = result["text"]
-        fakecaps.append({"image_id": int(image_id), "caption": caption})
-    return fakecaps
-
-
-def get_pred_idx(prediction, choices, options):
-    """
-    Get the index (e.g. 2) from the prediction (e.g. 'C')
-    """
-    if prediction in options[: len(choices)]:
-        return options.index(prediction)
-    else:
-        return random.choice(range(len(choices)))
-
-
-if __name__ == "__main__":
-    args = get_args()
-
-    base_dir = args.base_dir
-    split_indices = json.load(open(os.path.join(base_dir, "pid_splits.json")))[
-        args.split
-    ]
-    problems = json.load(open(os.path.join(base_dir, "problems.json")))
-    predictions = [json.loads(line) for line in open(args.result_file)]
-    predictions = {pred["question_id"]: pred for pred in predictions}
-    split_problems = {idx: problems[idx] for idx in split_indices}
-
-    results = {"correct": [], "incorrect": []}
-    sqa_results = {}
-    sqa_results["acc"] = None
-    sqa_results["correct"] = None
-    sqa_results["count"] = None
-    sqa_results["results"] = {}
-    sqa_results["outputs"] = {}
-
-    for prob_id, prob in split_problems.items():
-        if prob_id not in predictions:
-            continue
-        pred = predictions[prob_id]
-        pred_text = pred["text"]
-
-        pattern = re.compile(r"The answer is ([A-Z]).")
-        res = pattern.findall(pred_text)
-        if len(res) == 1:
-            answer = res[0]  # 'A', 'B', ...
-        else:
-            answer = "FAILED"
-
-        pred_idx = get_pred_idx(answer, prob["choices"], args.options)
-
-        analysis = {
-            "question_id": prob_id,
-            "parsed_ans": answer,
-            "ground_truth": args.options[prob["answer"]],
-            "question": pred["prompt"],
-            "pred": pred_text,
-            "is_multimodal": "<image>" in pred["prompt"],
-        }
-
-        sqa_results["results"][prob_id] = get_pred_idx(
-            answer, prob["choices"], args.options
-        )
-        sqa_results["outputs"][prob_id] = pred_text
-
-        if pred_idx == prob["answer"]:
-            results["correct"].append(analysis)
-        else:
-            results["incorrect"].append(analysis)
-
-    correct = len(results["correct"])
-    total = len(results["correct"]) + len(results["incorrect"])
-    print(f"Total: {total}, Correct: {correct}, Accuracy: {correct / total * 100:.2f}%")
-
-    sqa_results["acc"] = correct / total * 100
-    sqa_results["correct"] = correct
-    sqa_results["count"] = total
-
-    with open(args.output_file, "w") as f:
-        json.dump(results, f, indent=2)
-    with open(args.output_result, "w") as f:
-        json.dump(sqa_results, f, indent=2)

model/llava/eval/eval_science_qa_gpt4.py

@@ -1,108 +0,0 @@
-import argparse
-import json
-import os
-import random
-import re
-from collections import defaultdict
-
-
-def get_args():
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--base-dir", type=str)
-    parser.add_argument("--gpt4-result", type=str)
-    parser.add_argument("--our-result", type=str)
-    parser.add_argument("--split", type=str, default="test")
-    parser.add_argument("--options", type=list, default=["A", "B", "C", "D", "E"])
-    return parser.parse_args()
-
-
-def convert_caps(results):
-    fakecaps = []
-    for result in results:
-        image_id = result["question_id"]
-        caption = result["text"]
-        fakecaps.append({"image_id": int(image_id), "caption": caption})
-    return fakecaps
-
-
-def get_pred_idx(prediction, choices, options):
-    """
-    Get the index (e.g. 2) from the prediction (e.g. 'C')
-    """
-    if prediction in options[: len(choices)]:
-        return options.index(prediction)
-    else:
-        return random.choice(range(len(choices)))
-
-
-if __name__ == "__main__":
-    args = get_args()
-
-    base_dir = args.base_dir
-    split_indices = json.load(open(os.path.join(base_dir, "pid_splits.json")))[
-        args.split
-    ]
-    problems = json.load(open(os.path.join(base_dir, "problems.json")))
-    our_predictions = [json.loads(line) for line in open(args.our_result)]
-    our_predictions = {pred["question_id"]: pred for pred in our_predictions}
-    split_problems = {idx: problems[idx] for idx in split_indices}
-
-    gpt4_predictions = json.load(open(args.gpt4_result))["outputs"]
-
-    results = defaultdict(lambda: 0)
-
-    for prob_id, prob in split_problems.items():
-        if prob_id not in our_predictions:
-            continue
-        if prob_id not in gpt4_predictions:
-            continue
-        our_pred = our_predictions[prob_id]["text"]
-        gpt4_pred = gpt4_predictions[prob_id]
-
-        pattern = re.compile(r"The answer is ([A-Z]).")
-        our_res = pattern.findall(our_pred)
-        if len(our_res) == 1:
-            our_answer = our_res[0]  # 'A', 'B', ...
-        else:
-            our_answer = "FAILED"
-        gpt4_res = pattern.findall(gpt4_pred)
-        if len(gpt4_res) == 1:
-            gpt4_answer = gpt4_res[0]  # 'A', 'B', ...
-        else:
-            gpt4_answer = "FAILED"
-
-        our_pred_idx = get_pred_idx(our_answer, prob["choices"], args.options)
-        gpt4_pred_idx = get_pred_idx(gpt4_answer, prob["choices"], args.options)
-
-        if gpt4_answer == "FAILED":
-            results["gpt4_failed"] += 1
-            # continue
-            gpt4_pred_idx = our_pred_idx
-            # if our_pred_idx != prob['answer']:
-            #     print(our_predictions[prob_id]['prompt'])
-            #     print('-----------------')
-            #     print(f'LECTURE: {prob["lecture"]}')
-            #     print(f'SOLUTION: {prob["solution"]}')
-            #     print('=====================')
-        else:
-            # continue
-            pass
-        # gpt4_pred_idx = our_pred_idx
-
-        if gpt4_pred_idx == prob["answer"]:
-            results["correct"] += 1
-        else:
-            results["incorrect"] += 1
-
-        if gpt4_pred_idx == prob["answer"] or our_pred_idx == prob["answer"]:
-            results["correct_upperbound"] += 1
-
-    correct = results["correct"]
-    total = results["correct"] + results["incorrect"]
-    print(f"Total: {total}, Correct: {correct}, Accuracy: {correct / total * 100:.2f}%")
-    print(
-        f'Total: {total}, Correct (upper): {results["correct_upperbound"]}, Accuracy: {results["correct_upperbound"] / total * 100:.2f}%'
-    )
-    print(
-        f'Total: {total}, GPT-4 NO-ANS (RANDOM): {results["gpt4_failed"]}, Percentage: {results["gpt4_failed"] / total * 100:.2f}%'
-    )

model/llava/eval/eval_science_qa_gpt4_requery.py

@@ -1,164 +0,0 @@
-import argparse
-import json
-import os
-import random
-import re
-from collections import defaultdict
-
-
-def get_args():
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--base-dir", type=str)
-    parser.add_argument("--gpt4-result", type=str)
-    parser.add_argument("--requery-result", type=str)
-    parser.add_argument("--our-result", type=str)
-    parser.add_argument("--output-result", type=str)
-    parser.add_argument("--split", type=str, default="test")
-    parser.add_argument("--options", type=list, default=["A", "B", "C", "D", "E"])
-    return parser.parse_args()
-
-
-def convert_caps(results):
-    fakecaps = []
-    for result in results:
-        image_id = result["question_id"]
-        caption = result["text"]
-        fakecaps.append({"image_id": int(image_id), "caption": caption})
-    return fakecaps
-
-
-def get_pred_idx(prediction, choices, options):
-    """
-    Get the index (e.g. 2) from the prediction (e.g. 'C')
-    """
-    if prediction in options[: len(choices)]:
-        return options.index(prediction)
-    else:
-        return random.choice(range(len(choices)))
-
-
-if __name__ == "__main__":
-    args = get_args()
-
-    base_dir = args.base_dir
-    split_indices = json.load(open(os.path.join(base_dir, "pid_splits.json")))[
-        args.split
-    ]
-    problems = json.load(open(os.path.join(base_dir, "problems.json")))
-    our_predictions = [json.loads(line) for line in open(args.our_result)]
-    our_predictions = {pred["question_id"]: pred for pred in our_predictions}
-    split_problems = {idx: problems[idx] for idx in split_indices}
-
-    requery_predictions = [json.loads(line) for line in open(args.requery_result)]
-    requery_predictions = {pred["question_id"]: pred for pred in requery_predictions}
-
-    gpt4_predictions = json.load(open(args.gpt4_result))["outputs"]
-
-    results = defaultdict(lambda: 0)
-
-    sqa_results = {}
-    sqa_results["acc"] = None
-    sqa_results["correct"] = None
-    sqa_results["count"] = None
-    sqa_results["results"] = {}
-    sqa_results["outputs"] = {}
-
-    for prob_id, prob in split_problems.items():
-        if prob_id not in our_predictions:
-            assert False
-        if prob_id not in gpt4_predictions:
-            assert False
-        our_pred = our_predictions[prob_id]["text"]
-        gpt4_pred = gpt4_predictions[prob_id]
-        if prob_id not in requery_predictions:
-            results["missing_requery"] += 1
-            requery_pred = "MISSING"
-        else:
-            requery_pred = requery_predictions[prob_id]["text"]
-
-        pattern = re.compile(r"The answer is ([A-Z]).")
-        our_res = pattern.findall(our_pred)
-        if len(our_res) == 1:
-            our_answer = our_res[0]  # 'A', 'B', ...
-        else:
-            our_answer = "FAILED"
-
-        requery_res = pattern.findall(requery_pred)
-        if len(requery_res) == 1:
-            requery_answer = requery_res[0]  # 'A', 'B', ...
-        else:
-            requery_answer = "FAILED"
-
-        gpt4_res = pattern.findall(gpt4_pred)
-        if len(gpt4_res) == 1:
-            gpt4_answer = gpt4_res[0]  # 'A', 'B', ...
-        else:
-            gpt4_answer = "FAILED"
-
-        our_pred_idx = get_pred_idx(our_answer, prob["choices"], args.options)
-        gpt4_pred_idx = get_pred_idx(gpt4_answer, prob["choices"], args.options)
-        requery_pred_idx = get_pred_idx(requery_answer, prob["choices"], args.options)
-
-        results["total"] += 1
-
-        if gpt4_answer == "FAILED":
-            results["gpt4_failed"] += 1
-            if gpt4_pred_idx == prob["answer"]:
-                results["gpt4_correct"] += 1
-            if our_pred_idx == prob["answer"]:
-                results["gpt4_ourvisual_correct"] += 1
-        elif gpt4_pred_idx == prob["answer"]:
-            results["gpt4_correct"] += 1
-            results["gpt4_ourvisual_correct"] += 1
-
-        if our_pred_idx == prob["answer"]:
-            results["our_correct"] += 1
-
-        if requery_answer == "FAILED":
-            sqa_results["results"][prob_id] = our_pred_idx
-            if our_pred_idx == prob["answer"]:
-                results["requery_correct"] += 1
-        else:
-            sqa_results["results"][prob_id] = requery_pred_idx
-            if requery_pred_idx == prob["answer"]:
-                results["requery_correct"] += 1
-            else:
-                print(
-                    f"""
-Question ({args.options[prob['answer']]}): {our_predictions[prob_id]['prompt']}
-Our ({our_answer}): {our_pred}
-GPT-4 ({gpt4_answer}): {gpt4_pred}
-Requery ({requery_answer}): {requery_pred}
-print("=====================================")
-"""
-                )
-
-        if gpt4_pred_idx == prob["answer"] or our_pred_idx == prob["answer"]:
-            results["correct_upperbound"] += 1
-
-    total = results["total"]
-    print(
-        f'Total: {total}, Our-Correct: {results["our_correct"]}, Accuracy: {results["our_correct"] / total * 100:.2f}%'
-    )
-    print(
-        f'Total: {total}, GPT-4-Correct: {results["gpt4_correct"]}, Accuracy: {results["gpt4_correct"] / total * 100:.2f}%'
-    )
-    print(
-        f'Total: {total}, GPT-4 NO-ANS (RANDOM): {results["gpt4_failed"]}, Percentage: {results["gpt4_failed"] / total * 100:.2f}%'
-    )
-    print(
-        f'Total: {total}, GPT-4-OursVisual-Correct: {results["gpt4_ourvisual_correct"]}, Accuracy: {results["gpt4_ourvisual_correct"] / total * 100:.2f}%'
-    )
-    print(
-        f'Total: {total}, Requery-Correct: {results["requery_correct"]}, Accuracy: {results["requery_correct"] / total * 100:.2f}%'
-    )
-    print(
-        f'Total: {total}, Correct upper: {results["correct_upperbound"]}, Accuracy: {results["correct_upperbound"] / total * 100:.2f}%'
-    )
-
-    sqa_results["acc"] = results["requery_correct"] / total * 100
-    sqa_results["correct"] = results["requery_correct"]
-    sqa_results["count"] = total
-
-    with open(args.output_result, "w") as f:
-        json.dump(sqa_results, f, indent=2)

model/llava/eval/generate_webpage_data_from_table.py

@@ -1,119 +0,0 @@
-"""Generate json file for webpage."""
-import json
-import os
-import re
-
-# models = ['llama', 'alpaca', 'gpt35', 'bard']
-models = ["vicuna"]
-
-
-def read_jsonl(path: str, key: str = None):
-    data = []
-    with open(os.path.expanduser(path)) as f:
-        for line in f:
-            if not line:
-                continue
-            data.append(json.loads(line))
-    if key is not None:
-        data.sort(key=lambda x: x[key])
-        data = {item[key]: item for item in data}
-    return data
-
-
-def trim_hanging_lines(s: str, n: int) -> str:
-    s = s.strip()
-    for _ in range(n):
-        s = s.split("\n", 1)[1].strip()
-    return s
-
-
-if __name__ == "__main__":
-    questions = read_jsonl("table/question.jsonl", key="question_id")
-
-    # alpaca_answers = read_jsonl('table/answer/answer_alpaca-13b.jsonl', key='question_id')
-    # bard_answers = read_jsonl('table/answer/answer_bard.jsonl', key='question_id')
-    # gpt35_answers = read_jsonl('table/answer/answer_gpt35.jsonl', key='question_id')
-    # llama_answers = read_jsonl('table/answer/answer_llama-13b.jsonl', key='question_id')
-    vicuna_answers = read_jsonl(
-        "table/answer/answer_vicuna-13b.jsonl", key="question_id"
-    )
-    ours_answers = read_jsonl(
-        "table/results/llama-13b-hf-alpaca.jsonl", key="question_id"
-    )
-
-    review_vicuna = read_jsonl(
-        "table/review/review_vicuna-13b_llama-13b-hf-alpaca.jsonl", key="question_id"
-    )
-    # review_alpaca = read_jsonl('table/review/review_alpaca-13b_vicuna-13b.jsonl', key='question_id')
-    # review_bard = read_jsonl('table/review/review_bard_vicuna-13b.jsonl', key='question_id')
-    # review_gpt35 = read_jsonl('table/review/review_gpt35_vicuna-13b.jsonl', key='question_id')
-    # review_llama = read_jsonl('table/review/review_llama-13b_vicuna-13b.jsonl', key='question_id')
-
-    records = []
-    for qid in questions.keys():
-        r = {
-            "id": qid,
-            "category": questions[qid]["category"],
-            "question": questions[qid]["text"],
-            "answers": {
-                # 'alpaca': alpaca_answers[qid]['text'],
-                # 'llama': llama_answers[qid]['text'],
-                # 'bard': bard_answers[qid]['text'],
-                # 'gpt35': gpt35_answers[qid]['text'],
-                "vicuna": vicuna_answers[qid]["text"],
-                "ours": ours_answers[qid]["text"],
-            },
-            "evaluations": {
-                # 'alpaca': review_alpaca[qid]['text'],
-                # 'llama': review_llama[qid]['text'],
-                # 'bard': review_bard[qid]['text'],
-                "vicuna": review_vicuna[qid]["content"],
-                # 'gpt35': review_gpt35[qid]['text'],
-            },
-            "scores": {
-                "vicuna": review_vicuna[qid]["tuple"],
-                # 'alpaca': review_alpaca[qid]['score'],
-                # 'llama': review_llama[qid]['score'],
-                # 'bard': review_bard[qid]['score'],
-                # 'gpt35': review_gpt35[qid]['score'],
-            },
-        }
-
-        # cleanup data
-        cleaned_evals = {}
-        for k, v in r["evaluations"].items():
-            v = v.strip()
-            lines = v.split("\n")
-            # trim the first line if it's a pair of numbers
-            if re.match(r"\d+[, ]+\d+", lines[0]):
-                lines = lines[1:]
-            v = "\n".join(lines)
-            cleaned_evals[k] = v.replace("Assistant 1", "**Assistant 1**").replace(
-                "Assistant 2", "**Assistant 2**"
-            )
-
-        r["evaluations"] = cleaned_evals
-        records.append(r)
-
-    # Reorder the records, this is optional
-    for r in records:
-        if r["id"] <= 20:
-            r["id"] += 60
-        else:
-            r["id"] -= 20
-    for r in records:
-        if r["id"] <= 50:
-            r["id"] += 10
-        elif 50 < r["id"] <= 60:
-            r["id"] -= 50
-    for r in records:
-        if r["id"] == 7:
-            r["id"] = 1
-        elif r["id"] < 7:
-            r["id"] += 1
-
-    records.sort(key=lambda x: x["id"])
-
-    # Write to file
-    with open("webpage/data.json", "w") as f:
-        json.dump({"questions": records, "models": models}, f, indent=2)

model/llava/eval/model_qa.py

@@ -1,97 +0,0 @@
-import argparse
-import json
-import os
-
-import shortuuid
-import torch
-from llava.conversation import default_conversation
-from llava.utils import disable_torch_init
-from tqdm import tqdm
-from transformers import AutoModelForCausalLM, AutoTokenizer, StoppingCriteria
-
-
-# new stopping implementation
-class KeywordsStoppingCriteria(StoppingCriteria):
-    def __init__(self, keywords, tokenizer, input_ids):
-        self.keywords = keywords
-        self.tokenizer = tokenizer
-        self.start_len = None
-        self.input_ids = input_ids
-
-    def __call__(
-        self, output_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs
-    ) -> bool:
-        if self.start_len is None:
-            self.start_len = self.input_ids.shape[1]
-        else:
-            outputs = self.tokenizer.batch_decode(
-                output_ids[:, self.start_len :], skip_special_tokens=True
-            )[0]
-            for keyword in self.keywords:
-                if keyword in outputs:
-                    return True
-        return False
-
-
-@torch.inference_mode()
-def eval_model(model_name, questions_file, answers_file):
-    # Model
-    disable_torch_init()
-    model_name = os.path.expanduser(model_name)
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
-    model = AutoModelForCausalLM.from_pretrained(
-        model_name, torch_dtype=torch.float16
-    ).cuda()
-
-    ques_file = open(os.path.expanduser(questions_file), "r")
-    ans_file = open(os.path.expanduser(answers_file), "w")
-    for i, line in enumerate(tqdm(ques_file)):
-        idx = json.loads(line)["question_id"]
-        qs = json.loads(line)["text"]
-        cat = json.loads(line)["category"]
-        conv = default_conversation.copy()
-        conv.append_message(conv.roles[0], qs)
-        prompt = conv.get_prompt()
-        inputs = tokenizer([prompt])
-        input_ids = torch.as_tensor(inputs.input_ids).cuda()
-        stopping_criteria = KeywordsStoppingCriteria([conv.sep], tokenizer, input_ids)
-        output_ids = model.generate(
-            input_ids,
-            do_sample=True,
-            temperature=0.7,
-            max_new_tokens=1024,
-            stopping_criteria=[stopping_criteria],
-        )
-        outputs = tokenizer.batch_decode(output_ids, skip_special_tokens=True)[0]
-        try:
-            index = outputs.index(conv.sep, len(prompt))
-        except ValueError:
-            outputs += conv.sep
-            index = outputs.index(conv.sep, len(prompt))
-
-        outputs = outputs[len(prompt) + len(conv.roles[1]) + 2 : index].strip()
-        ans_id = shortuuid.uuid()
-        ans_file.write(
-            json.dumps(
-                {
-                    "question_id": idx,
-                    "text": outputs,
-                    "answer_id": ans_id,
-                    "model_id": model_name,
-                    "metadata": {},
-                }
-            )
-            + "\n"
-        )
-        ans_file.flush()
-    ans_file.close()
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--model-name", type=str, default="facebook/opt-350m")
-    parser.add_argument("--question-file", type=str, default="tables/question.jsonl")
-    parser.add_argument("--answers-file", type=str, default="answer.jsonl")
-    args = parser.parse_args()
-
-    eval_model(args.model_name, args.question_file, args.answers_file)

model/llava/eval/model_vqa.py

@@ -1,275 +0,0 @@
-import argparse
-import json
-import math
-import os
-import random
-
-import shortuuid
-import torch
-from llava import LlavaLlamaForCausalLM
-from llava.conversation import conv_templates
-from llava.utils import disable_torch_init
-from PIL import Image
-from tqdm import tqdm
-from transformers import (
-    AutoConfig,
-    AutoModelForCausalLM,
-    AutoTokenizer,
-    CLIPImageProcessor,
-    CLIPVisionModel,
-    StoppingCriteria,
-)
-
-
-def split_list(lst, n):
-    """Split a list into n (roughly) equal-sized chunks"""
-    chunk_size = math.ceil(len(lst) / n)  # integer division
-    return [lst[i : i + chunk_size] for i in range(0, len(lst), chunk_size)]
-
-
-def get_chunk(lst, n, k):
-    chunks = split_list(lst, n)
-    return chunks[k]
-
-
-DEFAULT_IMAGE_TOKEN = "<image>"
-DEFAULT_IMAGE_PATCH_TOKEN = "<im_patch>"
-DEFAULT_IM_START_TOKEN = "<im_start>"
-DEFAULT_IM_END_TOKEN = "<im_end>"
-
-
-def patch_config(config):
-    patch_dict = {
-        "use_mm_proj": True,
-        "mm_vision_tower": "openai/clip-vit-large-patch14",
-        "mm_hidden_size": 1024,
-    }
-
-    cfg = AutoConfig.from_pretrained(config)
-    if not hasattr(cfg, "mm_vision_tower"):
-        print(
-            f"`mm_vision_tower` not found in `{config}`, applying patch and save to disk."
-        )
-        for k, v in patch_dict.items():
-            setattr(cfg, k, v)
-        cfg.save_pretrained(config)
-
-
-def eval_model(args):
-    # Model
-    disable_torch_init()
-    model_name = os.path.expanduser(args.model_name)
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
-    if args.mm_projector is None:
-        patch_config(model_name)
-        model = LlavaLlamaForCausalLM.from_pretrained(
-            model_name, torch_dtype=torch.float16
-        ).cuda()
-        image_processor = CLIPImageProcessor.from_pretrained(
-            model.config.mm_vision_tower, torch_dtype=torch.float16
-        )
-
-        mm_use_im_start_end = getattr(model.config, "mm_use_im_start_end", False)
-        tokenizer.add_tokens([DEFAULT_IMAGE_PATCH_TOKEN], special_tokens=True)
-        if mm_use_im_start_end:
-            tokenizer.add_tokens(
-                [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN], special_tokens=True
-            )
-
-        vision_tower = model.model.vision_tower[0]
-        vision_tower.to(device="cuda", dtype=torch.float16)
-        vision_config = vision_tower.config
-        vision_config.im_patch_token = tokenizer.convert_tokens_to_ids(
-            [DEFAULT_IMAGE_PATCH_TOKEN]
-        )[0]
-        vision_config.use_im_start_end = mm_use_im_start_end
-        if mm_use_im_start_end:
-            (
-                vision_config.im_start_token,
-                vision_config.im_end_token,
-            ) = tokenizer.convert_tokens_to_ids(
-                [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN]
-            )
-        image_token_len = (vision_config.image_size // vision_config.patch_size) ** 2
-    else:
-        # in case of using a pretrained model with only a MLP projector weights
-        model = LlavaLlamaForCausalLM.from_pretrained(
-            model_name, torch_dtype=torch.float16
-        ).cuda()
-
-        vision_tower = CLIPVisionModel.from_pretrained(
-            args.vision_tower, torch_dtype=torch.float16
-        ).cuda()
-        image_processor = CLIPImageProcessor.from_pretrained(
-            args.vision_tower, torch_dtype=torch.float16
-        )
-
-        mm_use_im_start_end = getattr(model.config, "mm_use_im_start_end", False)
-        tokenizer.add_tokens([DEFAULT_IMAGE_PATCH_TOKEN], special_tokens=True)
-        if mm_use_im_start_end:
-            tokenizer.add_tokens(
-                [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN], special_tokens=True
-            )
-
-        vision_config = vision_tower.config
-        vision_config.im_patch_token = tokenizer.convert_tokens_to_ids(
-            [DEFAULT_IMAGE_PATCH_TOKEN]
-        )[0]
-        vision_config.use_im_start_end = mm_use_im_start_end
-        if mm_use_im_start_end:
-            (
-                vision_config.im_start_token,
-                vision_config.im_end_token,
-            ) = tokenizer.convert_tokens_to_ids(
-                [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN]
-            )
-
-        image_token_len = (vision_config.image_size // vision_config.patch_size) ** 2
-
-        mm_projector = torch.nn.Linear(
-            vision_config.hidden_size, model.config.hidden_size
-        )
-        mm_projector_weights = torch.load(args.mm_projector, map_location="cpu")
-        mm_projector.load_state_dict(
-            {k.split(".")[-1]: v for k, v in mm_projector_weights.items()}
-        )
-
-        model.model.mm_projector = mm_projector.cuda().half()
-        model.model.vision_tower = [vision_tower]
-
-    questions = [
-        json.loads(q) for q in open(os.path.expanduser(args.question_file), "r")
-    ]
-    questions = get_chunk(questions, args.num_chunks, args.chunk_idx)
-    answers_file = os.path.expanduser(args.answers_file)
-    os.makedirs(os.path.dirname(answers_file), exist_ok=True)
-    ans_file = open(answers_file, "w")
-    for i, line in enumerate(tqdm(questions)):
-        idx = line["question_id"]
-        image_file = line["image"]
-        qs = line["text"]
-        cur_prompt = qs
-        if mm_use_im_start_end:
-            qs = (
-                qs
-                + "\n"
-                + DEFAULT_IM_START_TOKEN
-                + DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-                + DEFAULT_IM_END_TOKEN
-            )
-        else:
-            qs = qs + "\n" + DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-
-        if args.conv_mode == "simple_legacy":
-            qs += "\n\n### Response:"
-        # conv = default_conversation.copy()
-        conv = conv_templates[args.conv_mode].copy()
-        conv.append_message(conv.roles[0], qs)
-        prompt = conv.get_prompt()
-        inputs = tokenizer([prompt])
-
-        image = Image.open(os.path.join(args.image_folder, image_file))
-        # image.save(os.path.join(save_image_folder, image_file))
-        image_tensor = image_processor.preprocess(image, return_tensors="pt")[
-            "pixel_values"
-        ][0]
-
-        input_ids = torch.as_tensor(inputs.input_ids).cuda()
-
-        # new stopping implementation
-        class KeywordsStoppingCriteria(StoppingCriteria):
-            def __init__(self, keywords, tokenizer, input_ids):
-                self.keywords = keywords
-                self.tokenizer = tokenizer
-                self.start_len = None
-                self.input_ids = input_ids
-
-            def __call__(
-                self, output_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs
-            ) -> bool:
-                if self.start_len is None:
-                    self.start_len = self.input_ids.shape[1]
-                else:
-                    outputs = self.tokenizer.batch_decode(
-                        output_ids[:, self.start_len :], skip_special_tokens=True
-                    )[0]
-                    for keyword in self.keywords:
-                        if keyword in outputs:
-                            return True
-                return False
-
-        keywords = ["###"]
-        stopping_criteria = KeywordsStoppingCriteria(keywords, tokenizer, input_ids)
-
-        with torch.inference_mode():
-            output_ids = model.generate(
-                input_ids,
-                images=image_tensor.unsqueeze(0).half().cuda(),
-                do_sample=True,
-                temperature=0.7,
-                max_new_tokens=1024,
-                stopping_criteria=[stopping_criteria],
-            )
-
-        input_token_len = input_ids.shape[1]
-        n_diff_input_output = (
-            (input_ids != output_ids[:, :input_token_len]).sum().item()
-        )
-        if n_diff_input_output > 0:
-            print(
-                f"[Warning] Sample {i}: {n_diff_input_output} output_ids are not the same as the input_ids"
-            )
-        outputs = tokenizer.batch_decode(
-            output_ids[:, input_token_len:], skip_special_tokens=True
-        )[0]
-
-        if args.conv_mode == "simple_legacy" or args.conv_mode == "simple":
-            while True:
-                cur_len = len(outputs)
-                outputs = outputs.strip()
-                for pattern in ["###", "Assistant:", "Response:"]:
-                    if outputs.startswith(pattern):
-                        outputs = outputs[len(pattern) :].strip()
-                if len(outputs) == cur_len:
-                    break
-
-        try:
-            index = outputs.index(conv.sep)
-        except ValueError:
-            outputs += conv.sep
-            index = outputs.index(conv.sep)
-
-        outputs = outputs[:index].strip()
-
-        ans_id = shortuuid.uuid()
-        ans_file.write(
-            json.dumps(
-                {
-                    "question_id": idx,
-                    "prompt": cur_prompt,
-                    "text": outputs,
-                    "answer_id": ans_id,
-                    "model_id": model_name,
-                    "metadata": {},
-                }
-            )
-            + "\n"
-        )
-        ans_file.flush()
-    ans_file.close()
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--model-name", type=str, default="facebook/opt-350m")
-    parser.add_argument("--image-folder", type=str, default="")
-    parser.add_argument("--question-file", type=str, default="tables/question.jsonl")
-    parser.add_argument("--answers-file", type=str, default="answer.jsonl")
-    parser.add_argument("--mm-projector", type=str, default=None)
-    parser.add_argument("--vision-tower", type=str, default=None)
-    parser.add_argument("--conv-mode", type=str, default="simple")
-    parser.add_argument("--num-chunks", type=int, default=1)
-    parser.add_argument("--chunk-idx", type=int, default=0)
-    args = parser.parse_args()
-
-    eval_model(args)

model/llava/eval/model_vqa_science.py

@@ -1,381 +0,0 @@
-import argparse
-import json
-import math
-import os
-import random
-
-import shortuuid
-import torch
-from llava import LlavaLlamaForCausalLM
-from llava.conversation import conv_templates
-from llava.utils import disable_torch_init
-from PIL import Image
-from tqdm import tqdm
-from transformers import (
-    AutoConfig,
-    AutoModelForCausalLM,
-    AutoTokenizer,
-    CLIPImageProcessor,
-    CLIPVisionModel,
-    StoppingCriteria,
-)
-
-
-def split_list(lst, n):
-    """Split a list into n (roughly) equal-sized chunks"""
-    chunk_size = math.ceil(len(lst) / n)  # integer division
-    return [lst[i : i + chunk_size] for i in range(0, len(lst), chunk_size)]
-
-
-def get_chunk(lst, n, k):
-    chunks = split_list(lst, n)
-    return chunks[k]
-
-
-DEFAULT_IMAGE_TOKEN = "<image>"
-DEFAULT_IMAGE_PATCH_TOKEN = "<im_patch>"
-DEFAULT_IM_START_TOKEN = "<im_start>"
-DEFAULT_IM_END_TOKEN = "<im_end>"
-
-
-detail_describe_instructions = [
-    "Describe the following image in detail.",
-    "Provide a detailed description of the given image.",
-    "Give an elaborate explanation of the image you see.",
-    "Share a comprehensive rundown of the presented image.",
-    "Offer a thorough analysis of the image.",
-    "Explain the various aspects of the image before you.",
-    "Clarify the contents of the displayed image with great detail.",
-    "Characterize the image using a well-detailed description.",
-    "Break down the elements of the image in a detailed manner.",
-    "Walk through the important details of the image.",
-    "Portray the image with a rich, descriptive narrative.",
-    "Narrate the contents of the image with precision.",
-    "Analyze the image in a comprehensive and detailed manner.",
-    "Illustrate the image through a descriptive explanation.",
-    "Examine the image closely and share its details.",
-    "Write an exhaustive depiction of the given image.",
-]
-
-concise_describe_instructions = [
-    "Describe the following image concisely.",
-    "Provide a brief description of the given image.",
-    "Offer a succinct explanation of the picture presented.",
-    "Summarize the visual content of the following image.",
-    "Give a short and clear explanation of the subsequent image.",
-    "Share a concise interpretation of the image provided.",
-    "Present a compact description of the photo's key features.",
-    "Relay a brief, clear account of the picture shown.",
-    "Render a clear and concise summary of the photo below.",
-    "Write a terse but informative summary of the following picture.",
-    "Create a compact narrative representing the image presented.",
-]
-
-prompt_pool = detail_describe_instructions + concise_describe_instructions
-
-prompt_pool = ["Describe the following image in detail."]
-
-
-def patch_config(config):
-    patch_dict = {
-        "use_mm_proj": True,
-        "mm_vision_tower": "openai/clip-vit-large-patch14",
-        "mm_hidden_size": 1024,
-    }
-
-    cfg = AutoConfig.from_pretrained(config)
-    if not hasattr(cfg, "mm_vision_tower"):
-        print(
-            f"`mm_vision_tower` not found in `{config}`, applying patch and save to disk."
-        )
-        for k, v in patch_dict.items():
-            setattr(cfg, k, v)
-        cfg.save_pretrained(config)
-
-
-# new stopping implementation
-class KeywordsStoppingCriteria(StoppingCriteria):
-    def __init__(self, keywords, tokenizer, input_ids):
-        self.keywords = keywords
-        self.tokenizer = tokenizer
-        self.start_len = None
-        self.input_ids = input_ids
-
-    def __call__(
-        self, output_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs
-    ) -> bool:
-        if self.start_len is None:
-            self.start_len = self.input_ids.shape[1]
-        else:
-            outputs = self.tokenizer.batch_decode(
-                output_ids[:, self.start_len :], skip_special_tokens=True
-            )[0]
-            for keyword in self.keywords:
-                if keyword in outputs:
-                    return True
-        return False
-
-
-def eval_model(args):
-    # Model
-    disable_torch_init()
-    model_name = os.path.expanduser(args.model_name)
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
-    if args.mm_projector is None:
-        patch_config(model_name)
-        model = LlavaLlamaForCausalLM.from_pretrained(
-            model_name, torch_dtype=torch.float16, use_cache=True
-        ).cuda()
-        image_processor = CLIPImageProcessor.from_pretrained(
-            model.config.mm_vision_tower, torch_dtype=torch.float16
-        )
-
-        mm_use_im_start_end = getattr(model.config, "mm_use_im_start_end", False)
-        tokenizer.add_tokens([DEFAULT_IMAGE_PATCH_TOKEN], special_tokens=True)
-        if mm_use_im_start_end:
-            tokenizer.add_tokens(
-                [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN], special_tokens=True
-            )
-
-        vision_tower = model.model.vision_tower[0]
-        vision_tower.to(device="cuda", dtype=torch.float16)
-        vision_config = vision_tower.config
-        vision_config.im_patch_token = tokenizer.convert_tokens_to_ids(
-            [DEFAULT_IMAGE_PATCH_TOKEN]
-        )[0]
-        vision_config.use_im_start_end = mm_use_im_start_end
-        if mm_use_im_start_end:
-            (
-                vision_config.im_start_token,
-                vision_config.im_end_token,
-            ) = tokenizer.convert_tokens_to_ids(
-                [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN]
-            )
-        image_token_len = (vision_config.image_size // vision_config.patch_size) ** 2
-    else:
-        # in case of using a pretrained model with only a MLP projector weights
-        model = LlavaLlamaForCausalLM.from_pretrained(
-            model_name, torch_dtype=torch.float16, use_cache=True
-        ).cuda()
-
-        mm_use_im_start_end = getattr(model.config, "mm_use_im_start_end", False)
-        tokenizer.add_tokens([DEFAULT_IMAGE_PATCH_TOKEN], special_tokens=True)
-        if mm_use_im_start_end:
-            tokenizer.add_tokens(
-                [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN], special_tokens=True
-            )
-
-        vision_tower = CLIPVisionModel.from_pretrained(
-            args.vision_tower, torch_dtype=torch.float16
-        ).cuda()
-        image_processor = CLIPImageProcessor.from_pretrained(
-            args.vision_tower, torch_dtype=torch.float16
-        )
-
-        vision_config = vision_tower.config
-        vision_config.im_patch_token = tokenizer.convert_tokens_to_ids(
-            [DEFAULT_IMAGE_PATCH_TOKEN]
-        )[0]
-        vision_config.use_im_start_end = mm_use_im_start_end
-        if mm_use_im_start_end:
-            (
-                vision_config.im_start_token,
-                vision_config.im_end_token,
-            ) = tokenizer.convert_tokens_to_ids(
-                [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN]
-            )
-
-        image_token_len = (vision_config.image_size // vision_config.patch_size) ** 2
-
-        mm_projector = torch.nn.Linear(
-            vision_config.hidden_size, model.config.hidden_size
-        )
-        mm_projector_weights = torch.load(args.mm_projector, map_location="cpu")
-        mm_projector.load_state_dict(
-            {k.split(".")[-1]: v for k, v in mm_projector_weights.items()}
-        )
-
-        model.model.mm_projector = mm_projector.cuda().half()
-        model.model.vision_tower = [vision_tower]
-
-    questions = json.load(open(os.path.expanduser(args.question_file), "r"))
-    questions = get_chunk(questions, args.num_chunks, args.chunk_idx)
-    answers_file = os.path.expanduser(args.answers_file)
-    os.makedirs(os.path.dirname(answers_file), exist_ok=True)
-    os.makedirs(os.path.join(os.path.dirname(answers_file), "images"), exist_ok=True)
-    ans_file = open(answers_file, "w")
-    save_image_folder = os.path.join(
-        os.path.dirname(os.path.expanduser(args.answers_file)), "images"
-    )
-    for i, line in enumerate(tqdm(questions)):
-        idx = line["id"]
-        question = line["conversations"][0]
-        gt_ans = line["conversations"][1]
-
-        qs = question["value"]
-
-        qs = qs.replace("<image>", "").strip()
-        cur_prompt = qs
-
-        if "image" in line:
-            image_file = line["image"]
-            image = Image.open(os.path.join(args.image_folder, image_file))
-            image_tensor = image_processor.preprocess(image, return_tensors="pt")[
-                "pixel_values"
-            ][0]
-            images = image_tensor.unsqueeze(0).half().cuda()
-            if getattr(model.config, "mm_use_im_start_end", False):
-                qs = (
-                    qs
-                    + "\n"
-                    + DEFAULT_IM_START_TOKEN
-                    + DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-                    + DEFAULT_IM_END_TOKEN
-                )
-            else:
-                qs = qs + "\n" + DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-            cur_prompt = cur_prompt + "\n" + "<image>"
-        else:
-            images = None
-
-        if args.conv_mode == "simple_legacy":
-            qs += "\n\n### Response:"
-        assert gt_ans["from"] == "gpt"
-        # conv = default_conversation.copy()
-        conv = conv_templates[args.conv_mode].copy()
-        conv.append_message(conv.roles[0], qs)
-        prompt = conv.get_prompt()
-        inputs = tokenizer([prompt])
-
-        input_ids = torch.as_tensor(inputs.input_ids).cuda()
-
-        keywords = ["###"]
-        stopping_criteria = KeywordsStoppingCriteria(keywords, tokenizer, input_ids)
-
-        with torch.inference_mode():
-            output_ids = model.generate(
-                input_ids,
-                images=images,
-                do_sample=True,
-                temperature=0.7,
-                max_new_tokens=1024,
-                stopping_criteria=[stopping_criteria],
-            )
-
-        # TODO: new implementation
-        input_token_len = input_ids.shape[1]
-        n_diff_input_output = (
-            (input_ids != output_ids[:, :input_token_len]).sum().item()
-        )
-        if n_diff_input_output > 0:
-            print(
-                f"[Warning] Sample {i}: {n_diff_input_output} output_ids are not the same as the input_ids"
-            )
-        outputs = tokenizer.batch_decode(
-            output_ids[:, input_token_len:], skip_special_tokens=True
-        )[0]
-
-        if args.conv_mode == "simple_legacy":
-            while True:
-                cur_len = len(outputs)
-                outputs = outputs.strip()
-                for pattern in ["###", "Assistant:", "Response:"]:
-                    if outputs.startswith(pattern):
-                        outputs = outputs[len(pattern) :].strip()
-                if len(outputs) == cur_len:
-                    break
-
-        try:
-            index = outputs.index(conv.sep)
-        except ValueError:
-            outputs += conv.sep
-            index = outputs.index(conv.sep)
-
-        outputs = outputs[:index].strip()
-
-        # prompt for answer
-        if args.answer_prompter:
-            outputs_reasoning = outputs
-            inputs = tokenizer([prompt + outputs_reasoning + " ###\nANSWER:"])
-
-            input_ids = torch.as_tensor(inputs.input_ids).cuda()
-
-            keywords = ["###"]
-            stopping_criteria = KeywordsStoppingCriteria(keywords, tokenizer, input_ids)
-
-            with torch.inference_mode():
-                output_ids = model.generate(
-                    input_ids,
-                    images=images,
-                    do_sample=True,
-                    temperature=0.7,
-                    max_new_tokens=64,
-                    stopping_criteria=[stopping_criteria],
-                )
-
-            input_token_len = input_ids.shape[1]
-            n_diff_input_output = (
-                (input_ids != output_ids[:, :input_token_len]).sum().item()
-            )
-            if n_diff_input_output > 0:
-                print(
-                    f"[Warning] Sample {i}: {n_diff_input_output} output_ids are not the same as the input_ids"
-                )
-            outputs = tokenizer.batch_decode(
-                output_ids[:, input_token_len:], skip_special_tokens=True
-            )[0]
-
-            try:
-                index = outputs.index(conv.sep)
-            except ValueError:
-                outputs += conv.sep
-                index = outputs.index(conv.sep)
-
-            outputs = outputs[:index].strip()
-            outputs = outputs_reasoning + "\n The answer is " + outputs
-
-        # new implementation ends
-
-        # original implementation
-        # outputs = tokenizer.batch_decode(output_ids, skip_special_tokens=True)[0]
-        # try:
-        #     index = outputs.index(conv.sep, len(prompt))
-        # except ValueError:
-        #     outputs += conv.sep
-        #     index = outputs.index(conv.sep, len(prompt))
-
-        # outputs = outputs[len(prompt) + len(conv.roles[1]) + 2:index].strip()
-
-        ans_id = shortuuid.uuid()
-        ans_file.write(
-            json.dumps(
-                {
-                    "question_id": idx,
-                    "prompt": cur_prompt,
-                    "text": outputs,
-                    "answer_id": ans_id,
-                    "model_id": model_name,
-                    "metadata": {},
-                }
-            )
-            + "\n"
-        )
-        ans_file.flush()
-    ans_file.close()
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--model-name", type=str, default="facebook/opt-350m")
-    parser.add_argument("--image-folder", type=str, default="")
-    parser.add_argument("--question-file", type=str, default="tables/question.json")
-    parser.add_argument("--answers-file", type=str, default="answer.jsonl")
-    parser.add_argument("--mm-projector", type=str, default=None)
-    parser.add_argument("--vision-tower", type=str, default=None)
-    parser.add_argument("--conv-mode", type=str, default="simple")
-    parser.add_argument("--num-chunks", type=int, default=1)
-    parser.add_argument("--chunk-idx", type=int, default=0)
-    parser.add_argument("--answer-prompter", action="store_true")
-    args = parser.parse_args()
-
-    eval_model(args)

model/llava/eval/qa_baseline_gpt35.py

@@ -1,82 +0,0 @@
-"""Generate answers with GPT-3.5"""
-# Note: you need to be using OpenAI Python v0.27.0 for the code below to work
-import argparse
-import concurrent.futures
-import json
-import os
-import time
-
-import openai
-import shortuuid
-import tqdm
-
-MODEL = "gpt-3.5-turbo"
-MODEL_ID = "gpt-3.5-turbo:20230327"
-
-
-def get_answer(question_id: int, question: str, max_tokens: int):
-    ans = {
-        "answer_id": shortuuid.uuid(),
-        "question_id": question_id,
-        "model_id": MODEL_ID,
-    }
-    for _ in range(3):
-        try:
-            response = openai.ChatCompletion.create(
-                model=MODEL,
-                messages=[
-                    {"role": "system", "content": "You are a helpful assistant."},
-                    {
-                        "role": "user",
-                        "content": question,
-                    },
-                ],
-                max_tokens=max_tokens,
-            )
-            ans["text"] = response["choices"][0]["message"]["content"]
-            return ans
-        except Exception as e:
-            print("[ERROR]", e)
-            ans["text"] = "#ERROR#"
-            time.sleep(1)
-    return ans
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser(description="ChatGPT answer generation.")
-    parser.add_argument("-q", "--question")
-    parser.add_argument("-o", "--output")
-    parser.add_argument(
-        "--max-tokens",
-        type=int,
-        default=1024,
-        help="maximum number of tokens produced in the output",
-    )
-    args = parser.parse_args()
-
-    questions_dict = {}
-    with open(os.path.expanduser(args.question)) as f:
-        for line in f:
-            if not line:
-                continue
-            q = json.loads(line)
-            questions_dict[q["question_id"]] = q["text"]
-
-    answers = []
-
-    with concurrent.futures.ThreadPoolExecutor(max_workers=32) as executor:
-        futures = []
-        for qid, question in questions_dict.items():
-            future = executor.submit(get_answer, qid, question, args.max_tokens)
-            futures.append(future)
-
-        for future in tqdm.tqdm(
-            concurrent.futures.as_completed(futures), total=len(futures)
-        ):
-            answers.append(future.result())
-
-    answers.sort(key=lambda x: x["question_id"])
-
-    with open(os.path.expanduser(args.output), "w") as f:
-        table = [json.dumps(ans) for ans in answers]
-        f.write("\n".join(table))

model/llava/eval/run_llava.py

@@ -1,171 +0,0 @@
-import argparse
-import os
-from io import BytesIO
-
-import requests
-import torch
-from llava.conversation import SeparatorStyle, conv_templates
-from llava.model import *
-from llava.model.utils import KeywordsStoppingCriteria
-from llava.utils import disable_torch_init
-from PIL import Image
-from transformers import (
-    AutoModelForCausalLM,
-    AutoTokenizer,
-    CLIPImageProcessor,
-    CLIPVisionModel,
-    StoppingCriteria,
-)
-
-DEFAULT_IMAGE_TOKEN = "<image>"
-DEFAULT_IMAGE_PATCH_TOKEN = "<im_patch>"
-DEFAULT_IM_START_TOKEN = "<im_start>"
-DEFAULT_IM_END_TOKEN = "<im_end>"
-
-
-def load_image(image_file):
-    if image_file.startswith("http") or image_file.startswith("https"):
-        response = requests.get(image_file)
-        image = Image.open(BytesIO(response.content)).convert("RGB")
-    else:
-        image = Image.open(image_file).convert("RGB")
-    return image
-
-
-def eval_model(args):
-    # Model
-    disable_torch_init()
-    model_name = os.path.expanduser(args.model_name)
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
-
-    if "mpt" in model_name.lower():
-        model = LlavaMPTForCausalLM.from_pretrained(
-            model_name,
-            low_cpu_mem_usage=True,
-            torch_dtype=torch.float16,
-            use_cache=True,
-        ).cuda()
-    else:
-        # model = LlavaLlamaForCausalLM.from_pretrained(model_name, low_cpu_mem_usage=True, torch_dtype=torch.float16, use_cache=True).cuda()
-        model = LlavaLlamaForCausalLM.from_pretrained(
-            model_name, torch_dtype=torch.float16, device_map="auto"
-        )  # .cuda()
-    image_processor = CLIPImageProcessor.from_pretrained(
-        model.config.mm_vision_tower, torch_dtype=torch.float16
-    )
-
-    mm_use_im_start_end = getattr(model.config, "mm_use_im_start_end", False)
-    tokenizer.add_tokens([DEFAULT_IMAGE_PATCH_TOKEN], special_tokens=True)
-    if mm_use_im_start_end:
-        tokenizer.add_tokens(
-            [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN], special_tokens=True
-        )
-
-    vision_tower = model.get_model().vision_tower[0]
-    if vision_tower.device.type == "meta":
-        vision_tower = CLIPVisionModel.from_pretrained(
-            vision_tower.config._name_or_path,
-            torch_dtype=torch.float16,
-            low_cpu_mem_usage=True,
-        ).cuda()
-        model.get_model().vision_tower[0] = vision_tower
-    else:
-        vision_tower.to(device="cuda", dtype=torch.float16)
-    vision_config = vision_tower.config
-    vision_config.im_patch_token = tokenizer.convert_tokens_to_ids(
-        [DEFAULT_IMAGE_PATCH_TOKEN]
-    )[0]
-    vision_config.use_im_start_end = mm_use_im_start_end
-    if mm_use_im_start_end:
-        (
-            vision_config.im_start_token,
-            vision_config.im_end_token,
-        ) = tokenizer.convert_tokens_to_ids(
-            [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN]
-        )
-    image_token_len = (vision_config.image_size // vision_config.patch_size) ** 2
-
-    qs = args.query
-    if mm_use_im_start_end:
-        qs = (
-            qs
-            + "\n"
-            + DEFAULT_IM_START_TOKEN
-            + DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-            + DEFAULT_IM_END_TOKEN
-        )
-    else:
-        qs = qs + "\n" + DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-
-    if "v1" in model_name.lower():
-        conv_mode = "llava_v1"
-    elif "mpt" in model_name.lower():
-        conv_mode = "mpt_multimodal"
-    else:
-        conv_mode = "multimodal"
-
-    if args.conv_mode is not None and conv_mode != args.conv_mode:
-        print(
-            "[WARNING] the auto inferred conversation mode is {}, while `--conv-mode` is {}, using {}".format(
-                conv_mode, args.conv_mode, args.conv_mode
-            )
-        )
-    else:
-        args.conv_mode = conv_mode
-
-    conv = conv_templates[args.conv_mode].copy()
-    conv.append_message(conv.roles[0], qs)
-    conv.append_message(conv.roles[1], None)
-    prompt = conv.get_prompt()
-    inputs = tokenizer([prompt])
-
-    image = load_image(args.image_file)
-    image_tensor = image_processor.preprocess(image, return_tensors="pt")[
-        "pixel_values"
-    ][0]
-
-    input_ids = torch.as_tensor(inputs.input_ids).cuda()
-
-    stop_str = conv.sep if conv.sep_style != SeparatorStyle.TWO else conv.sep2
-    keywords = [stop_str]
-    stopping_criteria = KeywordsStoppingCriteria(keywords, tokenizer, input_ids)
-
-    with torch.inference_mode():
-        output_ids = model.generate(
-            input_ids,
-            images=image_tensor.unsqueeze(0).half().cuda(),
-            do_sample=True,
-            temperature=0.2,
-            max_new_tokens=1024,
-            stopping_criteria=[stopping_criteria],
-        )
-
-    input_token_len = input_ids.shape[1]
-    n_diff_input_output = (input_ids != output_ids[:, :input_token_len]).sum().item()
-    if n_diff_input_output > 0:
-        print(
-            f"[Warning] {n_diff_input_output} output_ids are not the same as the input_ids"
-        )
-    outputs = tokenizer.batch_decode(
-        output_ids[:, input_token_len:], skip_special_tokens=True
-    )[0]
-    outputs = outputs.strip()
-    if outputs.endswith(stop_str):
-        outputs = outputs[: -len(stop_str)]
-    outputs = outputs.strip()
-    print(outputs)
-
-    import pdb
-
-    pdb.set_trace()
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--model-name", type=str, default="facebook/opt-350m")
-    parser.add_argument("--image-file", type=str, required=True)
-    parser.add_argument("--query", type=str, required=True)
-    parser.add_argument("--conv-mode", type=str, default=None)
-    args = parser.parse_args()
-
-    eval_model(args)

model/llava/eval/run_llava_batch.py

@@ -1,372 +0,0 @@
-import argparse
-import glob
-import json
-import os
-from io import BytesIO
-
-import numpy as np
-import requests
-import torch
-import tqdm
-from llava.conversation import SeparatorStyle, conv_templates
-from llava.model import *
-from llava.model.utils import KeywordsStoppingCriteria
-from llava.utils import disable_torch_init
-from PIL import Image
-from transformers import (
-    AutoModelForCausalLM,
-    AutoTokenizer,
-    CLIPImageProcessor,
-    CLIPVisionModel,
-    StoppingCriteria,
-)
-
-DEFAULT_IMAGE_TOKEN = "<image>"
-DEFAULT_IMAGE_PATCH_TOKEN = "<im_patch>"
-DEFAULT_IM_START_TOKEN = "<im_start>"
-DEFAULT_IM_END_TOKEN = "<im_end>"
-
-
-def load_image(image_file):
-    if image_file.startswith("http") or image_file.startswith("https"):
-        response = requests.get(image_file)
-        image = Image.open(BytesIO(response.content)).convert("RGB")
-    else:
-        image = Image.open(image_file).convert("RGB")
-    return image
-
-
-classes = [
-    "wall",
-    "building",
-    "sky",
-    "floor",
-    "tree",
-    "ceiling",
-    "road",
-    "bed",
-    "windowpane",
-    "grass",
-    "cabinet",
-    "sidewalk",
-    "person",
-    "earth",
-    "door",
-    "table",
-    "mountain",
-    "plant",
-    "curtain",
-    "chair",
-    "car",
-    "water",
-    "painting",
-    "sofa",
-    "shelf",
-    "house",
-    "sea",
-    "mirror",
-    "rug",
-    "field",
-    "armchair",
-    "seat",
-    "fence",
-    "desk",
-    "rock",
-    "wardrobe",
-    "lamp",
-    "bathtub",
-    "railing",
-    "cushion",
-    "base",
-    "box",
-    "column",
-    "signboard",
-    "chest of drawers",
-    "counter",
-    "sand",
-    "sink",
-    "skyscraper",
-    "fireplace",
-    "refrigerator",
-    "grandstand",
-    "path",
-    "stairs",
-    "runway",
-    "case",
-    "pool table",
-    "pillow",
-    "screen door",
-    "stairway",
-    "river",
-    "bridge",
-    "bookcase",
-    "blind",
-    "coffee table",
-    "toilet",
-    "flower",
-    "book",
-    "hill",
-    "bench",
-    "countertop",
-    "stove",
-    "palm",
-    "kitchen island",
-    "computer",
-    "swivel chair",
-    "boat",
-    "bar",
-    "arcade machine",
-    "hovel",
-    "bus",
-    "towel",
-    "light",
-    "truck",
-    "tower",
-    "chandelier",
-    "awning",
-    "streetlight",
-    "booth",
-    "television receiver",
-    "airplane",
-    "dirt track",
-    "apparel",
-    "pole",
-    "land",
-    "bannister",
-    "escalator",
-    "ottoman",
-    "bottle",
-    "buffet",
-    "poster",
-    "stage",
-    "van",
-    "ship",
-    "fountain",
-    "conveyer belt",
-    "canopy",
-    "washer",
-    "plaything",
-    "swimming pool",
-    "stool",
-    "barrel",
-    "basket",
-    "waterfall",
-    "tent",
-    "bag",
-    "minibike",
-    "cradle",
-    "oven",
-    "ball",
-    "food",
-    "step",
-    "tank",
-    "trade name",
-    "microwave",
-    "pot",
-    "animal",
-    "bicycle",
-    "lake",
-    "dishwasher",
-    "screen",
-    "blanket",
-    "sculpture",
-    "hood",
-    "sconce",
-    "vase",
-    "traffic light",
-    "tray",
-    "ashcan",
-    "fan",
-    "pier",
-    "crt screen",
-    "plate",
-    "monitor",
-    "bulletin board",
-    "shower",
-    "radiator",
-    "glass",
-    "clock",
-    "flag",
-]
-
-
-def eval_model(args):
-    # Model
-    disable_torch_init()
-    model_name = os.path.expanduser(args.model_name)
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
-
-    if "mpt" in model_name.lower():
-        model = LlavaMPTForCausalLM.from_pretrained(
-            model_name,
-            low_cpu_mem_usage=True,
-            torch_dtype=torch.float16,
-            use_cache=True,
-        ).cuda()
-    else:
-        # model = LlavaLlamaForCausalLM.from_pretrained(model_name, low_cpu_mem_usage=True, torch_dtype=torch.float16, use_cache=True).cuda()
-        model = LlavaLlamaForCausalLM.from_pretrained(
-            model_name, torch_dtype=torch.float16, device_map="auto"
-        )  # .cuda()
-    image_processor = CLIPImageProcessor.from_pretrained(
-        model.config.mm_vision_tower, torch_dtype=torch.float16
-    )
-
-    mm_use_im_start_end = getattr(model.config, "mm_use_im_start_end", False)
-    tokenizer.add_tokens([DEFAULT_IMAGE_PATCH_TOKEN], special_tokens=True)
-    if mm_use_im_start_end:
-        tokenizer.add_tokens(
-            [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN], special_tokens=True
-        )
-
-    vision_tower = model.get_model().vision_tower[0]
-    if vision_tower.device.type == "meta":
-        vision_tower = CLIPVisionModel.from_pretrained(
-            vision_tower.config._name_or_path,
-            torch_dtype=torch.float16,
-            low_cpu_mem_usage=True,
-        ).cuda()
-        model.get_model().vision_tower[0] = vision_tower
-    else:
-        vision_tower.to(device="cuda", dtype=torch.float16)
-    vision_config = vision_tower.config
-    vision_config.im_patch_token = tokenizer.convert_tokens_to_ids(
-        [DEFAULT_IMAGE_PATCH_TOKEN]
-    )[0]
-    vision_config.use_im_start_end = mm_use_im_start_end
-    if mm_use_im_start_end:
-        (
-            vision_config.im_start_token,
-            vision_config.im_end_token,
-        ) = tokenizer.convert_tokens_to_ids(
-            [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN]
-        )
-    image_token_len = (vision_config.image_size // vision_config.patch_size) ** 2
-
-    # paths for all images
-    images = sorted(
-        glob.glob("/mnt/proj74/xinlai/dataset/ade20k/images/training/*.jpg")
-    )
-    results = []
-    for i, image_file in enumerate(tqdm.tqdm(images)):
-        # if i == 2:
-        #     break
-
-        # if i % 100 == 0:
-        #     print("i: {}, len(images): {}".format(i, len(images)))
-
-        print("i: {}, len(images): {}".format(i, len(images)))
-
-        image = load_image(image_file)
-        image_tensor = image_processor.preprocess(image, return_tensors="pt")[
-            "pixel_values"
-        ][0]
-        image_tensor = image_tensor.unsqueeze(0).half().cuda()
-
-        label_file = image_file.replace("images", "annotations").replace(".jpg", ".png")
-        label = Image.open(label_file)
-        label = np.array(label)
-        label_unique = np.unique(label)
-        for label in label_unique:
-            if label == 0:
-                continue
-            class_id = label - 1
-            class_label = classes[class_id]
-            input_conv = "Can you describe the {} in this image?".format(class_label)
-            qs = input_conv
-
-            # qs = args.query
-            if mm_use_im_start_end:
-                qs = (
-                    qs
-                    + "\n"
-                    + DEFAULT_IM_START_TOKEN
-                    + DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-                    + DEFAULT_IM_END_TOKEN
-                )
-            else:
-                qs = qs + "\n" + DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-
-            if "v1" in model_name.lower():
-                conv_mode = "llava_v1"
-            elif "mpt" in model_name.lower():
-                conv_mode = "mpt_multimodal"
-            else:
-                conv_mode = "multimodal"
-
-            if args.conv_mode is not None and conv_mode != args.conv_mode:
-                print(
-                    "[WARNING] the auto inferred conversation mode is {}, while `--conv-mode` is {}, using {}".format(
-                        conv_mode, args.conv_mode, args.conv_mode
-                    )
-                )
-            else:
-                args.conv_mode = conv_mode
-
-            conv = conv_templates[args.conv_mode].copy()
-            conv.append_message(conv.roles[0], qs)
-            conv.append_message(conv.roles[1], None)
-            prompt = conv.get_prompt()
-            inputs = tokenizer([prompt])
-
-            # image = load_image(args.image_file)
-            # image = load_image(image_file)
-            # image_tensor = image_processor.preprocess(image, return_tensors='pt')['pixel_values'][0]
-
-            input_ids = torch.as_tensor(inputs.input_ids).cuda()
-
-            stop_str = conv.sep if conv.sep_style != SeparatorStyle.TWO else conv.sep2
-            keywords = [stop_str]
-            stopping_criteria = KeywordsStoppingCriteria(keywords, tokenizer, input_ids)
-
-            with torch.inference_mode():
-                output_ids = model.generate(
-                    input_ids,
-                    images=image_tensor,
-                    do_sample=True,
-                    temperature=0.2,
-                    max_new_tokens=512,  # 1024,
-                    stopping_criteria=[stopping_criteria],
-                )
-
-            input_token_len = input_ids.shape[1]
-            n_diff_input_output = (
-                (input_ids != output_ids[:, :input_token_len]).sum().item()
-            )
-            if n_diff_input_output > 0:
-                print(
-                    f"[Warning] {n_diff_input_output} output_ids are not the same as the input_ids"
-                )
-            outputs = tokenizer.batch_decode(
-                output_ids[:, input_token_len:], skip_special_tokens=True
-            )[0]
-            outputs = outputs.strip()
-            if outputs.endswith(stop_str):
-                outputs = outputs[: -len(stop_str)]
-            outputs = outputs.strip()
-
-            print("qs: {}, output: {}, image_file: {}".format(qs, outputs, image_file))
-
-            results.append(
-                {
-                    "image_id": image_file.split("/")[-1],
-                    "input": input_conv,
-                    "output": outputs,
-                }
-            )
-
-    with open("/mnt/proj74/xinlai/LLM/LLaVA/ade20k_conversations.json", "w+") as f:
-        json.dump(results, f)
-
-        # print(outputs)
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--model-name", type=str, default="facebook/opt-350m")
-    parser.add_argument("--image-file", type=str, required=True)
-    parser.add_argument("--query", type=str, required=True)
-    parser.add_argument("--conv-mode", type=str, default=None)
-    args = parser.parse_args()
-
-    eval_model(args)

model/llava/eval/run_llava_batch_v2.py

@@ -1,386 +0,0 @@
-import argparse
-import glob
-import json
-import os
-from io import BytesIO
-
-import numpy as np
-import requests
-import torch
-import tqdm
-from llava.conversation import SeparatorStyle, conv_templates
-from llava.model import *
-from llava.model.utils import KeywordsStoppingCriteria
-from llava.utils import disable_torch_init
-from PIL import Image
-from transformers import (
-    AutoModelForCausalLM,
-    AutoTokenizer,
-    CLIPImageProcessor,
-    CLIPVisionModel,
-    StoppingCriteria,
-)
-
-DEFAULT_IMAGE_TOKEN = "<image>"
-DEFAULT_IMAGE_PATCH_TOKEN = "<im_patch>"
-DEFAULT_IM_START_TOKEN = "<im_start>"
-DEFAULT_IM_END_TOKEN = "<im_end>"
-
-
-def load_image(image_file):
-    if image_file.startswith("http") or image_file.startswith("https"):
-        response = requests.get(image_file)
-        image = Image.open(BytesIO(response.content)).convert("RGB")
-    else:
-        image = Image.open(image_file).convert("RGB")
-    return image
-
-
-classes = [
-    "wall",
-    "building",
-    "sky",
-    "floor",
-    "tree",
-    "ceiling",
-    "road",
-    "bed",
-    "windowpane",
-    "grass",
-    "cabinet",
-    "sidewalk",
-    "person",
-    "earth",
-    "door",
-    "table",
-    "mountain",
-    "plant",
-    "curtain",
-    "chair",
-    "car",
-    "water",
-    "painting",
-    "sofa",
-    "shelf",
-    "house",
-    "sea",
-    "mirror",
-    "rug",
-    "field",
-    "armchair",
-    "seat",
-    "fence",
-    "desk",
-    "rock",
-    "wardrobe",
-    "lamp",
-    "bathtub",
-    "railing",
-    "cushion",
-    "base",
-    "box",
-    "column",
-    "signboard",
-    "chest of drawers",
-    "counter",
-    "sand",
-    "sink",
-    "skyscraper",
-    "fireplace",
-    "refrigerator",
-    "grandstand",
-    "path",
-    "stairs",
-    "runway",
-    "case",
-    "pool table",
-    "pillow",
-    "screen door",
-    "stairway",
-    "river",
-    "bridge",
-    "bookcase",
-    "blind",
-    "coffee table",
-    "toilet",
-    "flower",
-    "book",
-    "hill",
-    "bench",
-    "countertop",
-    "stove",
-    "palm",
-    "kitchen island",
-    "computer",
-    "swivel chair",
-    "boat",
-    "bar",
-    "arcade machine",
-    "hovel",
-    "bus",
-    "towel",
-    "light",
-    "truck",
-    "tower",
-    "chandelier",
-    "awning",
-    "streetlight",
-    "booth",
-    "television receiver",
-    "airplane",
-    "dirt track",
-    "apparel",
-    "pole",
-    "land",
-    "bannister",
-    "escalator",
-    "ottoman",
-    "bottle",
-    "buffet",
-    "poster",
-    "stage",
-    "van",
-    "ship",
-    "fountain",
-    "conveyer belt",
-    "canopy",
-    "washer",
-    "plaything",
-    "swimming pool",
-    "stool",
-    "barrel",
-    "basket",
-    "waterfall",
-    "tent",
-    "bag",
-    "minibike",
-    "cradle",
-    "oven",
-    "ball",
-    "food",
-    "step",
-    "tank",
-    "trade name",
-    "microwave",
-    "pot",
-    "animal",
-    "bicycle",
-    "lake",
-    "dishwasher",
-    "screen",
-    "blanket",
-    "sculpture",
-    "hood",
-    "sconce",
-    "vase",
-    "traffic light",
-    "tray",
-    "ashcan",
-    "fan",
-    "pier",
-    "crt screen",
-    "plate",
-    "monitor",
-    "bulletin board",
-    "shower",
-    "radiator",
-    "glass",
-    "clock",
-    "flag",
-]
-
-
-def eval_model(args):
-    # Model
-    disable_torch_init()
-    model_name = os.path.expanduser(args.model_name)
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
-
-    if "mpt" in model_name.lower():
-        model = LlavaMPTForCausalLM.from_pretrained(
-            model_name,
-            low_cpu_mem_usage=True,
-            torch_dtype=torch.float16,
-            use_cache=True,
-        ).cuda()
-    else:
-        # model = LlavaLlamaForCausalLM.from_pretrained(model_name, low_cpu_mem_usage=True, torch_dtype=torch.float16, use_cache=True).cuda()
-        model = LlavaLlamaForCausalLM.from_pretrained(
-            model_name, torch_dtype=torch.float16, device_map="auto"
-        )  # .cuda()
-    image_processor = CLIPImageProcessor.from_pretrained(
-        model.config.mm_vision_tower, torch_dtype=torch.float16
-    )
-
-    mm_use_im_start_end = getattr(model.config, "mm_use_im_start_end", False)
-    tokenizer.add_tokens([DEFAULT_IMAGE_PATCH_TOKEN], special_tokens=True)
-    if mm_use_im_start_end:
-        tokenizer.add_tokens(
-            [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN], special_tokens=True
-        )
-
-    vision_tower = model.get_model().vision_tower[0]
-    if vision_tower.device.type == "meta":
-        vision_tower = CLIPVisionModel.from_pretrained(
-            vision_tower.config._name_or_path,
-            torch_dtype=torch.float16,
-            low_cpu_mem_usage=True,
-        ).cuda()
-        model.get_model().vision_tower[0] = vision_tower
-    # else:
-    # vision_tower.to(device='cuda', dtype=torch.float16)
-    vision_config = vision_tower.config
-    vision_config.im_patch_token = tokenizer.convert_tokens_to_ids(
-        [DEFAULT_IMAGE_PATCH_TOKEN]
-    )[0]
-    vision_config.use_im_start_end = mm_use_im_start_end
-    if mm_use_im_start_end:
-        (
-            vision_config.im_start_token,
-            vision_config.im_end_token,
-        ) = tokenizer.convert_tokens_to_ids(
-            [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN]
-        )
-    image_token_len = (vision_config.image_size // vision_config.patch_size) ** 2
-
-    # paths for all images
-    images = sorted(
-        glob.glob("/mnt/proj74/xinlai/dataset/ade20k/images/training/*.jpg")
-    )
-    results = []
-    for i, image_file in enumerate(tqdm.tqdm(images)):
-        # if i == 2:
-        #     break
-
-        # if i % 100 == 0:
-        #     print("i: {}, len(images): {}".format(i, len(images)))
-
-        print("i: {}, len(images): {}".format(i, len(images)))
-
-        prompt_list = []
-        label_file = image_file.replace("images", "annotations").replace(".jpg", ".png")
-        label = Image.open(label_file)
-        label = np.array(label)
-        label_unique = np.unique(label)
-
-        image = load_image(image_file)
-        image_tensor = image_processor.preprocess(image, return_tensors="pt")[
-            "pixel_values"
-        ][0]
-        image_tensor = image_tensor.unsqueeze(0).half().cuda()
-
-        for label in label_unique:
-            if label == 0:
-                continue
-            class_id = label - 1
-            class_label = classes[class_id]
-            input_conv = "Can you describe the {} in this image?".format(class_label)
-            qs = input_conv
-
-            # qs = args.query
-            if mm_use_im_start_end:
-                qs = (
-                    qs
-                    + "\n"
-                    + DEFAULT_IM_START_TOKEN
-                    + DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-                    + DEFAULT_IM_END_TOKEN
-                )
-            else:
-                qs = qs + "\n" + DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-
-            if "v1" in model_name.lower():
-                conv_mode = "llava_v1"
-            elif "mpt" in model_name.lower():
-                conv_mode = "mpt_multimodal"
-            else:
-                conv_mode = "multimodal"
-
-            if args.conv_mode is not None and conv_mode != args.conv_mode:
-                print(
-                    "[WARNING] the auto inferred conversation mode is {}, while `--conv-mode` is {}, using {}".format(
-                        conv_mode, args.conv_mode, args.conv_mode
-                    )
-                )
-            else:
-                args.conv_mode = conv_mode
-
-            conv = conv_templates[args.conv_mode].copy()
-            conv.append_message(conv.roles[0], qs)
-            conv.append_message(conv.roles[1], None)
-            prompt = conv.get_prompt()
-            prompt_list.append(prompt)
-
-        # inputs = tokenizer([prompt])
-        inputs = tokenizer(prompt_list, padding=True)
-        image_tensor = image_tensor.expand(len(prompt_list), -1, -1, -1).contiguous()
-
-        # image = load_image(args.image_file)
-        # image = load_image(image_file)
-        # image_tensor = image_processor.preprocess(image, return_tensors='pt')['pixel_values'][0]
-
-        input_ids = torch.as_tensor(inputs.input_ids).cuda()
-
-        stop_str = conv.sep if conv.sep_style != SeparatorStyle.TWO else conv.sep2
-
-        print("stop_str: ", stop_str)
-
-        keywords = [stop_str]
-        stopping_criteria = KeywordsStoppingCriteria(keywords, tokenizer, input_ids)
-
-        with torch.inference_mode():
-            output_ids = model.generate(
-                input_ids,
-                images=image_tensor,
-                # do_sample=True,
-                # temperature=0.2,
-                max_new_tokens=512,  # 1024,
-                stopping_criteria=[stopping_criteria],
-            )
-
-        input_token_len = input_ids.shape[1]
-        n_diff_input_output = (
-            (input_ids != output_ids[:, :input_token_len]).sum().item()
-        )
-        if n_diff_input_output > 0:
-            print(
-                f"[Warning] {n_diff_input_output} output_ids are not the same as the input_ids"
-            )
-
-        outputs_list = []
-        for output_id in output_ids:
-            outputs = tokenizer.batch_decode(
-                output_id[:, input_token_len:], skip_special_tokens=True
-            )[0]
-            outputs = outputs.strip()
-            if outputs.endswith(stop_str):
-                outputs = outputs[: -len(stop_str)]
-            outputs = outputs.strip()
-            outputs_list.append(outputs)
-
-        for qs, outputs in zip(prompt_list, outputs_list):
-            print("qs: {}, output: {}, image_file: {}".format(qs, outputs, image_file))
-
-        results.append(
-            {
-                "image_id": image_file.split("/")[-1],
-                "input": prompt_list,
-                "output": outputs_list,
-            }
-        )
-
-    with open("/mnt/proj74/xinlai/LLM/LLaVA/ade20k_conversations.json", "w+") as f:
-        json.dump(results, f)
-
-        # print(outputs)
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--model-name", type=str, default="facebook/opt-350m")
-    parser.add_argument("--image-file", type=str, required=True)
-    parser.add_argument("--query", type=str, required=True)
-    parser.add_argument("--conv-mode", type=str, default=None)
-    args = parser.parse_args()
-
-    eval_model(args)

model/llava/eval/run_llava_batch_v3.py

@@ -1,388 +0,0 @@
-import argparse
-import glob
-import json
-import os
-from io import BytesIO
-
-import numpy as np
-import requests
-import torch
-import tqdm
-from llava.conversation import SeparatorStyle, conv_templates
-from llava.model import *
-from llava.model.utils import KeywordsStoppingCriteria
-from llava.utils import disable_torch_init
-from PIL import Image
-from transformers import (
-    AutoModelForCausalLM,
-    AutoTokenizer,
-    CLIPImageProcessor,
-    CLIPVisionModel,
-    StoppingCriteria,
-)
-
-DEFAULT_IMAGE_TOKEN = "<image>"
-DEFAULT_IMAGE_PATCH_TOKEN = "<im_patch>"
-DEFAULT_IM_START_TOKEN = "<im_start>"
-DEFAULT_IM_END_TOKEN = "<im_end>"
-
-
-def load_image(image_file):
-    if image_file.startswith("http") or image_file.startswith("https"):
-        response = requests.get(image_file)
-        image = Image.open(BytesIO(response.content)).convert("RGB")
-    else:
-        image = Image.open(image_file).convert("RGB")
-    return image
-
-
-classes = [
-    "wall",
-    "building",
-    "sky",
-    "floor",
-    "tree",
-    "ceiling",
-    "road",
-    "bed",
-    "windowpane",
-    "grass",
-    "cabinet",
-    "sidewalk",
-    "person",
-    "earth",
-    "door",
-    "table",
-    "mountain",
-    "plant",
-    "curtain",
-    "chair",
-    "car",
-    "water",
-    "painting",
-    "sofa",
-    "shelf",
-    "house",
-    "sea",
-    "mirror",
-    "rug",
-    "field",
-    "armchair",
-    "seat",
-    "fence",
-    "desk",
-    "rock",
-    "wardrobe",
-    "lamp",
-    "bathtub",
-    "railing",
-    "cushion",
-    "base",
-    "box",
-    "column",
-    "signboard",
-    "chest of drawers",
-    "counter",
-    "sand",
-    "sink",
-    "skyscraper",
-    "fireplace",
-    "refrigerator",
-    "grandstand",
-    "path",
-    "stairs",
-    "runway",
-    "case",
-    "pool table",
-    "pillow",
-    "screen door",
-    "stairway",
-    "river",
-    "bridge",
-    "bookcase",
-    "blind",
-    "coffee table",
-    "toilet",
-    "flower",
-    "book",
-    "hill",
-    "bench",
-    "countertop",
-    "stove",
-    "palm",
-    "kitchen island",
-    "computer",
-    "swivel chair",
-    "boat",
-    "bar",
-    "arcade machine",
-    "hovel",
-    "bus",
-    "towel",
-    "light",
-    "truck",
-    "tower",
-    "chandelier",
-    "awning",
-    "streetlight",
-    "booth",
-    "television receiver",
-    "airplane",
-    "dirt track",
-    "apparel",
-    "pole",
-    "land",
-    "bannister",
-    "escalator",
-    "ottoman",
-    "bottle",
-    "buffet",
-    "poster",
-    "stage",
-    "van",
-    "ship",
-    "fountain",
-    "conveyer belt",
-    "canopy",
-    "washer",
-    "plaything",
-    "swimming pool",
-    "stool",
-    "barrel",
-    "basket",
-    "waterfall",
-    "tent",
-    "bag",
-    "minibike",
-    "cradle",
-    "oven",
-    "ball",
-    "food",
-    "step",
-    "tank",
-    "trade name",
-    "microwave",
-    "pot",
-    "animal",
-    "bicycle",
-    "lake",
-    "dishwasher",
-    "screen",
-    "blanket",
-    "sculpture",
-    "hood",
-    "sconce",
-    "vase",
-    "traffic light",
-    "tray",
-    "ashcan",
-    "fan",
-    "pier",
-    "crt screen",
-    "plate",
-    "monitor",
-    "bulletin board",
-    "shower",
-    "radiator",
-    "glass",
-    "clock",
-    "flag",
-]
-
-
-def eval_model(args):
-    # Model
-    disable_torch_init()
-    model_name = os.path.expanduser(args.model_name)
-    tokenizer = AutoTokenizer.from_pretrained(model_name)
-
-    if "mpt" in model_name.lower():
-        model = LlavaMPTForCausalLM.from_pretrained(
-            model_name,
-            low_cpu_mem_usage=True,
-            torch_dtype=torch.float16,
-            use_cache=True,
-        ).cuda()
-    else:
-        # model = LlavaLlamaForCausalLM.from_pretrained(model_name, low_cpu_mem_usage=True, torch_dtype=torch.float16, use_cache=True).cuda()
-        model = LlavaLlamaForCausalLM.from_pretrained(
-            model_name, torch_dtype=torch.float16, device_map="auto"
-        )  # .cuda()
-    image_processor = CLIPImageProcessor.from_pretrained(
-        model.config.mm_vision_tower, torch_dtype=torch.float16
-    )
-
-    mm_use_im_start_end = getattr(model.config, "mm_use_im_start_end", False)
-    tokenizer.add_tokens([DEFAULT_IMAGE_PATCH_TOKEN], special_tokens=True)
-    if mm_use_im_start_end:
-        tokenizer.add_tokens(
-            [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN], special_tokens=True
-        )
-
-    vision_tower = model.get_model().vision_tower[0]
-    if vision_tower.device.type == "meta":
-        vision_tower = CLIPVisionModel.from_pretrained(
-            vision_tower.config._name_or_path,
-            torch_dtype=torch.float16,
-            low_cpu_mem_usage=True,
-        ).cuda()
-        model.get_model().vision_tower[0] = vision_tower
-    else:
-        vision_tower.to(device="cuda", dtype=torch.float16)
-    vision_config = vision_tower.config
-    vision_config.im_patch_token = tokenizer.convert_tokens_to_ids(
-        [DEFAULT_IMAGE_PATCH_TOKEN]
-    )[0]
-    vision_config.use_im_start_end = mm_use_im_start_end
-    if mm_use_im_start_end:
-        (
-            vision_config.im_start_token,
-            vision_config.im_end_token,
-        ) = tokenizer.convert_tokens_to_ids(
-            [DEFAULT_IM_START_TOKEN, DEFAULT_IM_END_TOKEN]
-        )
-    image_token_len = (vision_config.image_size // vision_config.patch_size) ** 2
-
-    # paths for all images
-    images = sorted(
-        glob.glob("/mnt/proj74/xinlai/dataset/ade20k/images/training/*.jpg")
-    )
-    start, end = args.range.split(",")
-    start, end = int(start), int(end)
-    images = images[start:end]
-    results = []
-    for i, image_file in enumerate(tqdm.tqdm(images)):
-        # if i == 2:
-        #     break
-
-        # if i % 100 == 0:
-        #     print("i: {}, len(images): {}".format(i, len(images)))
-
-        print("i: {}, len(images): {}".format(i, len(images)))
-
-        image = load_image(image_file)
-        image_tensor = image_processor.preprocess(image, return_tensors="pt")[
-            "pixel_values"
-        ][0]
-        image_tensor = image_tensor.unsqueeze(0).half().cuda()
-
-        prompt_list = []
-        output_list = []
-
-        label_file = image_file.replace("images", "annotations").replace(".jpg", ".png")
-        label = Image.open(label_file)
-        label = np.array(label)
-        label_unique = np.unique(label)
-        for label in label_unique:
-            if label == 0:
-                continue
-            class_id = label - 1
-            class_label = classes[class_id]
-            input_conv = "Can you describe the {} in this image?".format(class_label)
-            qs = input_conv
-            prompt_list.append(input_conv)
-
-            # qs = args.query
-            if mm_use_im_start_end:
-                qs = (
-                    qs
-                    + "\n"
-                    + DEFAULT_IM_START_TOKEN
-                    + DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-                    + DEFAULT_IM_END_TOKEN
-                )
-            else:
-                qs = qs + "\n" + DEFAULT_IMAGE_PATCH_TOKEN * image_token_len
-
-            if "v1" in model_name.lower():
-                conv_mode = "llava_v1"
-            elif "mpt" in model_name.lower():
-                conv_mode = "mpt_multimodal"
-            else:
-                conv_mode = "multimodal"
-
-            if args.conv_mode is not None and conv_mode != args.conv_mode:
-                print(
-                    "[WARNING] the auto inferred conversation mode is {}, while `--conv-mode` is {}, using {}".format(
-                        conv_mode, args.conv_mode, args.conv_mode
-                    )
-                )
-            else:
-                args.conv_mode = conv_mode
-
-            conv = conv_templates[args.conv_mode].copy()
-            conv.append_message(conv.roles[0], qs)
-            conv.append_message(conv.roles[1], None)
-            prompt = conv.get_prompt()
-            inputs = tokenizer([prompt])
-
-            # image = load_image(args.image_file)
-            # image = load_image(image_file)
-            # image_tensor = image_processor.preprocess(image, return_tensors='pt')['pixel_values'][0]
-
-            input_ids = torch.as_tensor(inputs.input_ids).cuda()
-
-            stop_str = conv.sep if conv.sep_style != SeparatorStyle.TWO else conv.sep2
-            keywords = [stop_str]
-            stopping_criteria = KeywordsStoppingCriteria(keywords, tokenizer, input_ids)
-
-            with torch.inference_mode():
-                output_ids = model.generate(
-                    input_ids,
-                    images=image_tensor,
-                    do_sample=True,
-                    temperature=0.2,
-                    max_new_tokens=512,  # 1024,
-                    stopping_criteria=[stopping_criteria],
-                )
-
-            input_token_len = input_ids.shape[1]
-            n_diff_input_output = (
-                (input_ids != output_ids[:, :input_token_len]).sum().item()
-            )
-            if n_diff_input_output > 0:
-                print(
-                    f"[Warning] {n_diff_input_output} output_ids are not the same as the input_ids"
-                )
-            outputs = tokenizer.batch_decode(
-                output_ids[:, input_token_len:], skip_special_tokens=True
-            )[0]
-            outputs = outputs.strip()
-            if outputs.endswith(stop_str):
-                outputs = outputs[: -len(stop_str)]
-            outputs = outputs.strip()
-
-            # print("qs: {}, output: {}, image_file: {}".format(qs, outputs, image_file))
-
-            # image_id = image_file.split("/")[-1]
-            # results.append({'image_id': image_id, 'input': input_conv, 'output': outputs})
-            output_list.append(outputs)
-        image_id = image_file.split("/")[-1].split(".")[0]
-        with open(
-            "/mnt/proj74/xinlai/LLM/LLaVA/generated/{}.json".format(image_id), "w+"
-        ) as f:
-            json.dump(
-                {
-                    "image_id": image_id,
-                    "input_list": prompt_list,
-                    "output_list": output_list,
-                },
-                f,
-            )
-
-    # with open("/mnt/proj74/xinlai/LLM/LLaVA/ade20k_conversations.json", "w+") as f:
-    #     json.dump(results, f)
-
-    # print(outputs)
-
-
-if __name__ == "__main__":
-    parser = argparse.ArgumentParser()
-    parser.add_argument("--model-name", type=str, default="facebook/opt-350m")
-    parser.add_argument("--image-file", type=str, required=True)
-    parser.add_argument("--query", type=str, required=True)
-    parser.add_argument("--conv-mode", type=str, default=None)
-    parser.add_argument("--range", type=str, default=None)
-    args = parser.parse_args()
-
-    eval_model(args)

model/llava/eval/summarize_gpt_review.py

@@ -1,28 +0,0 @@
-import json
-import os
-from collections import defaultdict
-
-import numpy as np
-
-if __name__ == "__main__":
-    base_dir = "vqa/reviews/coco2014_val80"
-    review_files = [
-        x
-        for x in os.listdir(base_dir)
-        if x.endswith(".jsonl") and x.startswith("gpt4_text")
-    ]
-
-    for review_file in sorted(review_files):
-        config = review_file.replace("gpt4_text_", "").replace(".jsonl", "")
-        scores = defaultdict(list)
-        print(f"GPT-4 vs. {config}")
-        with open(os.path.join(base_dir, review_file)) as f:
-            for review_str in f:
-                review = json.loads(review_str)
-                scores[review["category"]].append(review["tuple"])
-                scores["all"].append(review["tuple"])
-        for k, v in scores.items():
-            stats = np.asarray(v).mean(0).tolist()
-            stats = [round(x, 3) for x in stats]
-            print(k, stats, round(stats[1] / stats[0] * 100, 1))
-        print("=================================")

model/llava/eval/table/answer/answer_alpaca-13b.jsonl

@@ -1,80 +0,0 @@
-{"question_id": 1, "text": "Improving time management skills involves setting priorities, breaking tasks into smaller chunks, delegating tasks, avoiding multitasking, and taking regular breaks. Additionally, it is important to have a positive attitude and be realistic with goals. Making a to-do list, tracking time, and using technology to automate mundane tasks can also help improve time management skills.", "answer_id": "kEL9ifUHDeYuAXzevje2se", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 2, "text": "The most effective ways to deal with stress include identifying and avoiding the sources of stress, developing healthy coping mechanisms, and engaging in relaxation techniques such as meditation, deep breathing, and physical exercise. Additionally, it is important to take care of one's mental and physical health, get enough rest and nutrition, and practice self-care.", "answer_id": "VcF3NrWGXhhxLkDVurNrwq", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 3, "text": "The main differences between Python and JavaScript programming languages are in their syntax, structure, and the type of applications they are designed for. Python is a general-purpose language designed to be easy to read and write, while JavaScript is primarily used for web development. Python is a compiled language, while JavaScript is an interpreted language. Python is strongly typed, while JavaScript is not. Python is typically faster than JavaScript in terms of execution, while JavaScript is better suited to create interactive web pages.", "answer_id": "LpvtyQi9QdSgRrgGDxiGrT", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 4, "text": "Working from home can be a great way to increase productivity, but it does require some strategic planning and tactics. Here are some tips for increasing your productivity while working from home: \n1. Establish a routine: Having a regular schedule and sticking to it can help you stay focused and motivated.\n2. Create a distraction-free zone: Eliminate distractions by turning off notifications and setting a \u201cdo not disturb\u201d mode.\n3. Take breaks: Working for long stretches without taking breaks can lead to burnout and decreased productivity.\n4. Exercise: Exercise can help improve focus and productivity.\n5. Get organized: Having a clean and organized workspace can help you stay on task.\n6. Set goals: Set short-term and long-term goals to keep you motivated and on track.\n7. Connect with colleagues: Don\u2019t be afraid to reach out to colleagues for help or advice.\n8. Track your progress: Keep track of your progress and celebrate your successes.\n9. Unplug: Taking breaks and unplugging from work can help you recharge and come back to work more refreshed.", "answer_id": "7zQm8cSTJhPtPdZdxbcfrX", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 5, "text": "Sure. Quantum computing is a new technology that uses quantum mechanical phenomena to perform operations on data. Unlike traditional computers, which process information in binary form, quantum computers can process information in multiple states at the same time, allowing them to perform operations faster and with more accuracy. It also allows them to solve problems that classical computers struggle with. Quantum computing is still in its infancy, but it has the potential to revolutionize the computing industry and open up new possibilities in artificial intelligence, cryptography, and other fields.", "answer_id": "UrLEH82RHwqqLt2LyvYSKj", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 6, "text": "Plant-based protein sources include legumes, grains, nuts, and seeds, and are generally lower in fat and calories than animal-based proteins. Animal-based proteins come from sources such as meat, eggs, and dairy, and are generally higher in fat and calories than plant-based proteins. Plant-based proteins are also generally lower in cholesterol and saturated fat than animal-based proteins. Additionally, plant-based proteins require fewer resources for production, such as water and land, than animal-based proteins.", "answer_id": "fpRdMTdnfirosQixuf2Gez", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 7, "text": "Developing critical thinking skills involves actively questioning assumptions, taking multiple perspectives, analyzing information, and coming to logical conclusions. You can practice these skills by posing questions to yourself and working through problems, as well as engaging in thoughtful discussion with others.", "answer_id": "PvGmsCJSNFcvQKmPTnnd7s", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 8, "text": "The major challenges faced by the education sector include lack of access to quality education, low educational outcomes, high costs of education, lack of adequate infrastructure and teaching materials, overcrowding in classrooms, and gender inequality. Other challenges include lack of access to technology and digital learning materials, outdated curriculum and pedagogical practices, and inadequate teacher training.", "answer_id": "n4ANAbpR3gvLPP8poPfKZ6", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 9, "text": "The primary factors that influence consumer behavior include cultural, social, and personal factors. Cultural factors include shared beliefs, values, and customs within a society, while social factors include the influence of family, friends, and peers. Personal factors include an individual's lifestyle, attitudes, beliefs, and past experiences. Other factors such as advertising, marketing, and price also have an effect on consumer behavior.", "answer_id": "STJ36GrgQMcaUi7zaoNPit", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 10, "text": "The most effective strategies for conflict resolution in the workplace include:\n1. Establishing open communication: Encouraging open and honest communication between parties is key to resolving any conflict.\n2. Listening actively: Active listening allows both parties to feel heard and allows for a better understanding of the other person's perspective.\n3. Identifying root causes: Understanding the underlying cause of the conflict can help to find more effective solutions that address the core issue.\n4. Focusing on interests, not positions: Focusing on the interests of both parties can help to find creative solutions that satisfy the needs of everyone involved.\n5. Developing mutual respect: Respect is essential to any successful resolution. Building mutual respect can help to create a healthier work environment.\n6. Negotiation: Working together to negotiate a mutually beneficial solution can help to create an agreement that both parties are happy with.\n7. Taking responsibility: Taking responsibility for one\u2019s words and actions can help to create a culture of accountability in the workplace.", "answer_id": "425SwYvqKPAXFGTYKXB7Cs", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 11, "text": "The use of single-use plastic bottles has a number of negative implications on the environment. They are not biodegradable and can take hundreds of years to break down. This means they are around for a long time, releasing potentially harmful chemicals into the environment, and they can be easily mistaken for food by animals. Single-use plastic bottles can also be a source of micro-plastics, which are very small particles of plastic that are difficult to clean up and can be consumed by fish and other aquatic life, leading to health problems in humans who consume those fish. On the other hand, reusable bottles are a much more environmentally friendly choice since they do not produce any waste. They are also often made of materials that are safer for human health, such as stainless steel or glass. Reusable bottles are also more cost-effective since they do not need to be replaced as often as single-use plastic bottles.", "answer_id": "VbNAuj6KAkMdLJQXMo22oK", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 12, "text": "When designing an inclusive and accessible public transportation system, some factors to consider include providing frequent and reliable service, accessible stops and vehicles, a variety of fare options, clear and consistent signage and information, comfortable seating and space for wheelchairs and other assistive devices, and security and safety protocols. Additionally, public transportation systems should be integrated with other services such as public parking, bike and scooter sharing, and shuttles to provide a comprehensive and accessible experience.", "answer_id": "CNGqAeu2QJbQ4QGzHJDPdq", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 13, "text": "Governments can use fiscal and monetary policies to combat economic recessions. Fiscal policies involve the government spending money or cutting taxes in order to stimulate the economy, while monetary policies involve changing the money supply or interest rates to influence economic activity. These policies can be used to stabilize the economy, create jobs, and reduce poverty.", "answer_id": "E8w2qYqnm8iqCrSkUv62sz", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 14, "text": "Language and cultural barriers can lead to misunderstandings and make it more difficult to communicate and form relationships in multicultural societies. Without a common language or shared culture, people can have difficulty understanding each other's perspectives and beliefs, which can lead to mistrust and a lack of understanding between different ethnic groups. To overcome these barriers, it is important to make an effort to learn about different cultures, be open-minded, and take the time to understand each other.", "answer_id": "8o5yMymfzo6kzmp9GK5MWr", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 15, "text": "Artificial intelligence can be used to improve the quality and efficiency of healthcare delivery in a variety of ways. AI can be used to assist with diagnosing diseases by comparing symptoms and medical history to images of known diseases and medical conditions. AI can also be used to analyze laboratory results and patient records to identify potential problems and develop treatment plans. AI can be used to automate administrative tasks and reduce paperwork, as well as identify potential drug interactions and side effects. AI can also be used to automate appointment reminders, facilitate communication between doctors and patients, and even provide virtual health coaching to help patients manage their conditions.", "answer_id": "kbJVEEsdsSScEq5Y5furr7", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 16, "text": "CRISPR-Cas9 is a recently developed gene editing technology that has revolutionized the way scientists are able to edit genomes. The technology uses a guide RNA to direct the Cas9 enzyme to a specific location in the genome, where it will cut the DNA strands. This allows for the insertion or deletion of DNA sequences, which can be used to modify the genetic code of an organism. Potential applications include treating genetic diseases, increasing crop yields, and creating pest-resistant crops. Ethically, the biggest concern is the potential misuse of the technology, which could lead to unintended consequences or be used to alter humanity in ways that could harm us.", "answer_id": "CMUL5ULZuR7YC5EPzCBN2N", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 17, "text": "Vaccinations work by stimulating the body's immune system to protect against infectious diseases. Herd immunity is a concept whereby a population is protected against a certain disease when a certain percentage of the population has immunity to the disease, either through vaccination or having already contracted the disease. This is because when enough people are vaccinated, it reduces the spread of the disease and prevents it from spreading to those who are not immune.", "answer_id": "kEmDDQyNqSkyFihYEEBpuR", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 18, "text": "Social media platforms can have a significant influence on how people consume and share news. By providing instant access to news sources and allowing users to easily share content, these platforms can shape the public's information landscape and the spread of misinformation. Some potential implications of this are that users may not always be able to discern between reliable and unreliable sources, and misleading information may be more easily spread and go viral. This can lead to confusion and mistrust among users, and can potentially be exploited for nefarious purposes. To mitigate these risks, it is important for users to be aware of the potential biases and agendas of the sources they are consuming, and for social media platforms to take proactive steps to curb the spread of misinformation.", "answer_id": "Qs3grQsqFVGK9EVkCkf9PB", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 19, "text": "Cultural, social, and economic factors all play a role in determining an individual's food choices. For example, people growing up in households with limited economic means may be more likely to consume cheaper, less nutritious foods due to economic constraints. Additionally, cultural norms and values can influence food choices, such as the emphasis on large portions typical in some American cultural settings. Finally, social factors such as peer pressure and advertising can also sway an individual's food choices. By understanding and taking into account these various factors, health promotion strategies can be tailored and targeted to help individuals make healthier dietary decisions.", "answer_id": "kzZ6dKN7hkRWjqtdHr7Qns", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 20, "text": "Natural selection is the process by which certain traits or characteristics become more or less common in a population over time. This is due to the fact that those individuals with certain advantageous traits are more likely to survive, reproduce, and pass those traits on to their offspring. Over time, this leads to the evolution and adaptation of species to their environment.", "answer_id": "DPPDG6YGFJij2GCmRL66PU", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 21, "text": "I am a brave knight, loyal to my king and country, and I have come to serve and protect them both. I am skilled in the arts of war and peace, and I am proud to be here at the royal court.", "answer_id": "D62FjDb4nZANzPpfSfsiyn", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 22, "text": "Avast ye maties! To the bottom of the sea we go! In search of hidden riches and fortune, we shall brave the depths and face any danger that comes our way. For glory and honor, let us set sail and find the lost Ark!", "answer_id": "k7E4NNw5kyj9DmvP5Pu2zb", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 23, "text": "If I were a Shakespearean character, I would declare my love for someone in a soliloquy with passionate words and metaphors. I would express my love for them with descriptions of their beauty and the joy I feel when I am with them. I would confess my hopes and dreams for our future together and declare my devotion to them. I would make my love for them known in a way that could never be forgotten.", "answer_id": "KFocjVCejYrU3YmLjAqoUF", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 24, "text": "As a superhero, my origin story is very special. I was born with special abilities that I had to keep hidden for a long time. I was scared to use them at first, but eventually I discovered that I could use my powers to protect people and make the world a better place. I've had to face a lot of challenges along the way, but I've also had a lot of help from friends and family. Now, I use my abilities to help people in need and fight for justice.", "answer_id": "dq8Sm9djS7e7y9sG9vmMJf", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 25, "text": "If I were a time traveler from the year 3000, I would tell people about the incredible advancements in technology, such as the ability to travel through time, space, and dimensions; the development of intelligent robots and autonomous vehicles; the emergence of virtual reality and augmented reality; and the rise of artificial intelligence and machine learning.", "answer_id": "XZ8fG8e6u7CyKd2moK6abe", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 26, "text": "The game was a nail-biter, with both teams trading leads throughout the game. With only seconds left on the clock, the home team made a bold move and passed the ball to their star player, who took the ball down the court and made a layup at the buzzer to seal the victory for the home team!", "answer_id": "oKaXHfoK4pXwrefFWXmeA8", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 27, "text": "My signature dish is a seamless blend of traditional and modern cooking techniques. I use only the freshest ingredients to create a unique and unforgettable dining experience. The dish is a perfect balance of flavors and textures, with a subtle hint of my personal style. It is a dish that I am proud to call my own.", "answer_id": "ZwiZfvDWm7SETKNBfDk7Mb", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 28, "text": "At the summit of Mount Everest, you are filled with a sense of accomplishment and joy. The view from the top is absolutely breathtaking - you can see for miles and miles, with the majestic Himalayan mountain range stretching out in all directions. It is a truly unforgettable experience.", "answer_id": "DxYopRe2LcTJMy3FWu6btd", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 29, "text": "As a colonist on Mars, my daily life is filled with challenges. Finding resources and creating a sustainable environment is a priority. I face a number of challenges including extreme temperature fluctuations, limited access to resources, and the difficulty of travelling to and from the planet. Additionally, I must be mindful of my physical and mental health since I am so far from home. Despite these challenges, I am grateful to be able to explore and experience this new world.", "answer_id": "WC3UJVh4jQ5RUkpcRMU98L", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 30, "text": "In the post-apocalyptic world, I am a survivor by necessity. I scavenge for food and supplies, and I'm always on the lookout for potential allies. I've encountered a few people who have managed to survive, and together we have formed an alliance to help each other. We hunt for food, build shelter, and work together to stay alive. We also share knowledge and skills, like how to start a fire or how to use a weapon. We look out for each other, and our alliance has strengthened our chances of survival.", "answer_id": "gTvgn6ksDjGGgdprw6AG5A", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 31, "text": "There are a few ways to tell if a restaurant is popular among locals or mainly attracts tourists. Firstly, look at the clientele - if the majority of people there are tourists, it's likely that the restaurant is mainly attracting tourists. Secondly, check online reviews - if the reviews are mainly from tourists, then it's likely that the restaurant is popular with tourists. Finally, look at the prices - if the prices are higher than average for the area, it could be a sign that the restaurant is popular with locals. This information can be useful to get an idea of what kind of experience to expect, as locals might know about different aspects of the restaurant that tourists wouldn't.", "answer_id": "3q7giCk2BA3Ye4Tm9HC2iw", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 32, "text": "Some subtle clues that suggest someone is pretending to understand a topic or conversation when they are actually confused or uninformed include: not asking any questions or engaging in the conversation, avoiding eye contact, fidgeting or stammering when speaking, repeating questions or comments made by other people, and nodding along without any signs of understanding.", "answer_id": "hRGsxy86v26SC4yAQS29X4", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 33, "text": "Some people prefer the tactile and visual experience of using a paper map, and others may prefer to ask for directions from locals in order to get a more personalized experience. Additionally, GPS devices and smartphone apps can sometimes be inaccurate or have limited battery life, while a paper map or asking for directions may be more reliable.", "answer_id": "3n49A5ggJERfXYrLns3ZeU", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 34, "text": "One way to tell if someone is genuinely interested in a conversation is to observe their body language and facial expressions. Are they making an effort to maintain eye contact? Are they leaning in and actively listening to what you are saying? Do they ask questions and provide relevant answers? If so, it is likely that they are genuinely interested in the conversation. Additionally, if someone is simply being polite, they may not ask questions or engage in the conversation as much, and may not make an effort to maintain eye contact.", "answer_id": "ErCpFtPuYVru4oTTk4WrxG", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 35, "text": "Shopping at a small, locally-owned business can benefit the local community by keeping money in the area and supporting local jobs. Additionally, these businesses tend to offer a more personal experience and higher quality products than large chain stores. Furthermore, shopping at small businesses can help create a sense of place and community, and can help maintain a unique local culture.", "answer_id": "PTNoCRMZWoJk8HaKX7fW45", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 36, "text": "There are several ways to assess the credibility of a source of information. Firstly, you can look at the author's credentials and experience in the relevant field. Secondly, you can check the source of the information, such as whether it is from a reliable website or publication. Thirdly, you can look at the evidence presented in the article and whether it is backed up by reliable sources. Finally, you can read other people's reviews or comments about the article to get a better idea of its credibility.", "answer_id": "n8cFs9KENNwZ4z3SR4iXTr", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 37, "text": "Some people enjoy the sensation of being scared because it can create a feeling of excitement, enhance their emotional state, and provide a sense of thrill and adventure. Others may avoid these experiences because they are afraid of the unknown, or because they don't enjoy the feeling of being scared. Everyone is different, and some people may be more attracted to thrilling and exciting activities while others may prefer calmer activities.", "answer_id": "GzxL9mmEK5RzKqRbqBMUVC", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 38, "text": "By observing the behavior of others in a social situation, one can gain clues as to the cultural norms and expectations of a group. For example, watching how people interact with one another, how they address each other, how they handle disagreements, and how they go about solving problems can provide insight into the cultural values of the group. Additionally, observing body language, facial expressions, and other nonverbal cues can offer clues as to the accepted norms of behavior in a particular culture.", "answer_id": "QpoHFgb9SzwuaXQQUuBUQD", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 39, "text": "It is an interesting question, and one that has been debated for quite some time. I think there are valid arguments on both sides. On the one hand, exploring space is a remarkable human endeavor and could lead to tremendous scientific discoveries and technological advances. On the other hand, there are many pressing issues that need to be addressed on Earth, such as poverty, inequality, and climate change. Each side would argue that their cause is more important, and it is ultimately up to each individual to decide which one they feel more strongly about.", "answer_id": "Fxe6MS4GpP3LMDUwzY2cPA", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 40, "text": "It is important to strike a balance between job creation and technological progress. Automation can increase efficiency and productivity, but it should not come at the expense of job security and people's livelihoods. Therefore, it is essential to create policies and initiatives that promote both job creation and technological progress. This could include investing in training and education to ensure that people have the skills necessary to compete in the modern job market, as well as incentivizing companies to invest in technologies that create jobs and stimulate economic growth.", "answer_id": "mJiQ2FGR4Xb8kmhZjharkw", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 41, "text": "On average, the human eye blinks about 20 times per minute, or about 14,400 times per day. In a lifetime, this means that the average human will blink roughly 50 million times. This may seem like a lot, but it serves an important purpose. Blinking helps to keep the eyes lubricated and prevents them from drying out. It also helps to spread tears over the surface of the eye, washing away foreign particles and keeping the eye clean. Additionally, blinking helps to reduce the risk of eye infections by helping to clear away bacteria and other foreign substances.", "answer_id": "6Kph4RHRKEZ4YUoaHuEhBv", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 42, "text": "A grain of salt contains 102.98 atoms. To calculate this, we first need to know the atomic weight of a single atom. The atomic weight of an atom is the number of protons and neutrons in the nucleus of an atom, which determines its atomic mass. The atomic weight of a single atom of salt is 58.943 g/atom. Therefore, a grain of salt contains 102.98 atoms, which is equivalent to 60.98 grams.", "answer_id": "WBwpBQwhxn5kxLDb7MschC", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 43, "text": "Approximately 2000 lightning strikes occur on Earth each day. This is because the atmospheric conditions must come together in a particular way for a lightning strike to occur. Firstly, a large amount of electric charge must accumulate in the atmosphere, typically in a storm system. Then, the air must become increasingly unstable, leading to rising air and a strong updraft. This causes an electric breakdown of the air, and then an exchange of electricity occurs from the cloud to the ground, forming a lightning bolt. As these conditions are necessary for a lightning strike to occur, about 2000 lightning strikes happen on Earth each day.", "answer_id": "kf8nahQVci2ZLaYikagB7U", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 44, "text": "It would take about 10 million balloons to lift a house like in the movie Up. The balloons would need to be filled with helium in order for the house to be lifted. Each balloon would need to be filled with about 89.1 cubic feet of helium in order to lift 500 pounds. To calculate how many balloons would be needed, simply multiply the weight of the house (264.72 lbs) by the number of cubic feet of helium needed to lift 500 pounds (89.1). Therefore, it would take 10 million balloons to lift a house like in the movie Up.", "answer_id": "Gptgryd4o2dC8V5aqRmeJJ", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 45, "text": "According to a 2017 study, over 6.3 billion text messages are sent globally in a minute. This number is expected to grow to 6.8 billion by 2021. This is due to the increasing number of smartphones, better network coverage, and the increasing popularity of texting for communication. Furthermore, the increase in smartphones and better network coverage has also led to the rise of instant messaging applications such as WhatsApp, which has further increased the amount of text messages sent per minute.", "answer_id": "RfBWW8ZhdfTuTMb454Un4o", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 46, "text": "It is estimated that over 1 billion words are spoken on Earth every day. This is due to the fact that humans are highly social creatures, and language is the primary way that we communicate with each other. In addition, language is a key component of all cultures and societies, and is constantly being used to exchange information and ideas. Furthermore, language is integral to the way we think and process information, as well as to how we connect with each other on an emotional level. Therefore, it is not surprising that so many words are spoken on a daily basis.", "answer_id": "neGgLYm47JvqN8qkw8VeoW", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 47, "text": "On average, about 100 snowflakes fall per second during a typical winter. This number can vary drastically depending on the location and severity of the storm. Snowflakes are made up of tiny ice crystals, which form in the atmosphere when the temperature is below freezing and there is moisture in the air. As air moves and mixes, the crystals come together to form snowflakes. The shape, size and number of snowflakes depend on the atmospheric conditions, such as temperature and humidity, when they form.", "answer_id": "KSePbzLwsYasR3aui4HU8h", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 48, "text": "It is estimated that all the books ever written would total about 100 billion pages. This is based on the fact that there are roughly 130 million unique titles in existence, and each book on average contains about 200 pages. This means that if all the books were printed out, the stack of paper would be about 400 miles high. Additionally, if each book was represented by a single page, the total number of pages would be approximately 100 billion. Throughout history, books have served as a way to preserve knowledge and information, as well as to share ideas and stories with others. As technology advances, books are increasingly available in digital formats, which allows for easier access and storage. Regardless of the medium, books will continue to be a valuable source of information for generations to come.", "answer_id": "SWWfLpP2gnWHLbYRZXNsW3", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 49, "text": "Since the beginning of life, the Earth has orbited the Sun a total of 4.3 billion times. This is calculated by multiplying the average length of a year (365.25 days) by the number of years since life began (approximately 4.5 billion years). Life on Earth relies on the Sun's energy reaching the Earth's atmosphere and being redistributed by the atmosphere, the land surface, and the oceans. Without this energy, life on Earth would not be possible. Therefore, the Earth's orbit around the Sun is integral to the sustainability of life on Earth.", "answer_id": "WaBwKYhs7eAG22qCGLH2j3", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 50, "text": "Since the beginning of recorded music, countless songs have been recorded. The exact number is difficult to quantify, but conservative estimates put the number of songs recorded throughout history at several hundred thousand. This includes songs from all genres, from classical music to modern pop. The invention of recording technology has allowed musicians to preserve their music and share it with the world. This has enabled generations to access and enjoy music from all eras. With the rise of digital music, the number of recordings available has grown exponentially, and new songs are being recorded all the time.", "answer_id": "MfMJeE9om7qyBbqopHouf4", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 51, "text": "If the Internet had been invented during the Renaissance period, it likely would have been used primarily by the wealthy and powerful to access knowledge and information, as there was no widespread system of public education at the time. It also would have been a much slower and more expensive process to access information, as there were no high-speed connections or digital networks available.", "answer_id": "TjWPRDM6JFpPF8xeRptCKb", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 52, "text": "If the Aztecs had successfully repelled the Spanish conquistadors, their culture and way of life would have likely remained intact. The Spanish would not have been able to colonize Mexico, and their influence on the region would have been much less. It's likely that the Aztecs would have continued to expand their empire and control the areas that are now parts of Central and South America. Additionally, the Native American populations in the area would have likely been able to maintain more of their traditional customs and beliefs, and their languages may not have been as heavily impacted by Spanish.", "answer_id": "iR2tYTsWTFENEP7Qy9RgtX", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 53, "text": "If the Black Death had not occurred in the 14th century, the population of Europe may have continued to grow unabated, leading to more rapid urbanization and economic growth. It's likely that the Renaissance would have begun sooner, and the scientific revolution may have occurred earlier as well. Without the Black Death, there may have been no need for the industrial revolution, or at least it may have occurred later and on a smaller scale. Additionally, the spread of diseases may have been slower, leading to greater population density in certain areas.", "answer_id": "AZdS8xAi3GwAmCqkNSnnwv", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 54, "text": "If Isaac Newton had focused on biology instead of physics, he might have made important discoveries in the field of medicine and biology. He may have studied the human body and its functions in greater detail, and possibly even made important breakthroughs in treating diseases. He may also have studied the behavior of different animals in the wild and made important observations about their habits and habitats.", "answer_id": "VmwifF2JD5osYKDTqv2ZRS", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 55, "text": "If the Beatles had never formed as a band, the music world would have been drastically different. The British Invasion of the 1960s might not have happened, or it could have happened in a much different way. The cultural impact of the Beatles, including their influence on other musicians, fashion and society, may never have existed.", "answer_id": "mUL5UPj3qDGaCriEjL2U3B", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 56, "text": "If Alan Turing had not cracked the Enigma code during World War II, the outcome of the war could have been very different. It's possible that the Allies would have eventually defeated the Axis powers, but it likely would have taken much longer and cost many more lives. With the Enigma code cracked, the Allies were able to gain a critical advantage over the Axis powers and ultimately win the war.", "answer_id": "dVdwUoVrAQJDuWxiodykiw", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 57, "text": "If the Suez Canal had never been constructed, it would have major implications for international trade and navigation. The Suez Canal is an important shipping route connecting the Mediterranean Sea to the Red Sea, which in turn connects to the Indian Ocean. This allows for a shorter and more direct route for ships traveling between Europe and Asia, reducing travel time significantly. Without the Suez Canal, ships would have to travel around the Cape of Good Hope at the southern tip of Africa, which is much more time consuming and costly. This would make international trade more difficult and expensive, and could hinder global economic growth.", "answer_id": "EiNn9jjfy7dga6xfCtLtF8", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 58, "text": "If the Maya civilization had not mysteriously collapsed, it is likely that their influence and power would have continued to grow. They would have likely continued to build large cities and monuments, develop their writing and astronomical systems, and expand their trade networks. Additionally, their advances in agriculture and water management may have led to increased food production and a larger population.", "answer_id": "eqG9f2R9hXVyZrZMpcqAYq", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 59, "text": "If Christopher Columbus had not discovered the Americas, the indigenous people of the Americas would have continued to live in relative isolation from the rest of the world. It is likely that European colonization and the consequences of that would have been delayed, leading to a different modern world. It is also possible that other Europeans would have made the voyage across the Atlantic and discovered the Americas instead.", "answer_id": "ex42CLEzDVC2TxAvMCtYQJ", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 60, "text": "If Vincent van Gogh had been successful during his lifetime, he may have been able to achieve the recognition and financial stability that he desired. He may have been able to travel and gain more exposure for his artwork, as well as connect with other like-minded individuals. He may have been able to create more artwork and expand his portfolio. He may also have been able to find a mentor or patron who could have helped him further his career.", "answer_id": "RfFANSwHeCm3Pqe2AJ86Dk", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 61, "text": "The program should read a text file line by line. It should then check each line for the specified word, counting up each time the word is found. Finally, it should output the number of occurrences of the word.", "answer_id": "nzxdtWmgQhRkHeVAanVogZ", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 62, "text": "The following Python function can be used to find the longest common subsequence of two input strings using dynamic programming:\ndef longest_common_subsequence(s1, s2):\n\"\"\"This function finds the longest common subsequence of two strings.\n\n Arguments:\n    s1 {string} -- The first string\n    s2 {string} -- The second string\n\n Returns:\n    {int} -- The length of the longest common subsequence\n\n\"\"\"\n    n1 = len(s1)\n    n2 = len(s2)\n  \n    # Creating an empty matrix to store the results\n    results = [[None]*(n2 + 1) for _ in range(n1 + 1)]\n  \n    # Initializing the first row to 0\n    for i in range(n1 + 1):\n        results[i][0] = 0\n  \n    # Filling the first row with 0\n    for i in range(n1):\n        results[i][0] = 0\n  \n    # Calculating the longest common subsequence\n    for i in range(n1 + 1):\n        for j in range(n2 + 1):\n            if (i == 0 or j == 0):\n                results[i][j] = 0\n            elif (s1[i-1] == s2[j-1] and (results[i-1][j-1] < (i-j) or results[i-1][j-1] == 0)):\n                results[i][j] = max(results[i-1][j-1] + 1, i+j)\n            else:\n                results[i][j] = 0\n  \n    return results[n1][n2]", "answer_id": "kRo6z5qmeiSM8Xz6BPJHLC", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 63, "text": "The following regular expression can be used to validate an email address in Python:\n^[a-zA-Z0-9_.+-]+@[a-zA-Z0-9-]+\\.[a-zA-Z0-9-.]+$", "answer_id": "7kj8odEE79UBdR4pT6u6TY", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 64, "text": "Here is a program to find the nth Fibonacci number using dynamic programming:\n1. Set a variable 'n' to the nth Fibonacci number.\n2. Set two other variables 'a' and 'b' to 0 and 1 respectively.\n3. Set a loop from 0 to (n-1).\n4. In the loop, set another loop from 0 to (a+b).\n5. In the inner loop, if 'a' is even and 'b' is odd, set 'a' to a+1 and 'b' to b+1.\n6. If 'a' is odd and 'b' is even, set 'a' to a-1 and 'b' to b-1.\n7. After the inner loop, set 'n' to 'a' and break out of the outer loop.\n8. Print the value of 'n'.\nThis program uses the idea of dynamic programming to compute the nth Fibonacci number. The program first sets two auxiliary variables 'a' and 'b' to 0 and 1 respectively. Then it sets a loop from 0 to (n-1). In the loop, it sets another loop from 0 to (a+b). In the inner loop, if 'a' is even and 'b' is odd, it sets 'a' to a+1 and 'b' to b+1. If 'a' is odd and 'b' is even, it sets 'a' to a-1 and 'b' to b-1. After the inner loop, it sets 'n' to 'a' and breaks out of the outer loop. Finally, it prints the value of 'n'.", "answer_id": "UULZ4GLz9j9ot7tN7x3ySD", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 65, "text": "A binary search algorithm can be used to find a specific element in a sorted array by repeatedly splitting the array in half and examining the middle element to determine whether the target element is greater than, less than, or equal to it. If the target element is found, the algorithm immediately returns the index of the element. If it isn\u2019t, the array is split in half, with one half discarded based on the comparison. The process is repeated until the element is found or the array is completely searched.", "answer_id": "Rh8P3bxSJx4p6nCZkSZBrh", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 66, "text": "Implementing a queue using two stacks in Python is relatively simple. First, you need to create two stacks, which will act as the queue. Next, you need to define an enqueue and dequeue method, which will add and remove items from the queue. Finally, you need to create an instance of the queue class and start using it.", "answer_id": "R3aYUUtY46ht4ToU8US96x", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 67, "text": "The program can be implemented using two nested for loops. The inner loop can be used to iterate through the elements of the first array, while the outer loop can be used to iterate through the elements of the second array. If the two elements being compared are the same, the program should mark those elements with a \"found\" flag and move on. Once the inner loop completes, the program should check if the \"found\" flag is set for all elements in the second array. If it is, then the common elements have been found.", "answer_id": "MQJFbH3KoFaSMmPgmK9LPa", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 68, "text": "The value of f(2) is 1.", "answer_id": "dBWqryuzG6BHRdPgrWWpbH", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 69, "text": "x = 6.", "answer_id": "W74byrCbE7XiJWjcPTZS7x", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 70, "text": "The length of the line segment is 8 units.", "answer_id": "7WC5quGKdv8hADCxWaWZ57", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 71, "text": "Yes, I can help you write a formal email to a potential business partner proposing a joint venture. Here's a template that you can use:\nSubject Line: Proposing a Joint Venture\nDear [Name],\nI am writing to propose a joint venture between our two companies. I believe that by combining our resources, we can create a powerful and profitable partnership. Our combined experience and knowledge in the industry will help us to create something unique and special.\nI am confident that our partnership will bring mutual benefits, such as increased profits and access to new markets. Please let me know if you are interested, and we can discuss the details.\nThank you for your time and consideration. I look forward to hearing from you soon.\nSincerely,\n[Your Name]", "answer_id": "AZER7D3RKZ9F9SXHiMjdqM", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 72, "text": "Yes, I can help you write a resignation letter to your current employer. The letter should be written in a polite and professional tone and should express your appreciation for the opportunities and experiences you have gained during your employment. It should also include a clear statement of your intention to resign and the date of your last day. Here is a template you can use:\nDear [Employer],\nI am writing to inform you of my intention to resign from my position as [Position], effective [date]. I have appreciated my time here and I am grateful for the opportunities and experiences I have gained during my employment. \nI thank you for your support and understanding.\nSincerely, [Your Name]", "answer_id": "MSrdDafr77UvSHCnsPMSP3", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 73, "text": "The letter of recommendation should be structured in a formal manner. Begin by introducing the student and explaining your relationship to them. Describe their qualifications, including their academic performance and relevant skills, and mention any particular accomplishments or awards they have received. Explain why the student is a strong candidate for the program and how they will make a positive contribution. End the letter by reaffirming your recommendation and offering your contact information for further questions.", "answer_id": "hxkjUkDkXhGP78Vo74B4WE", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 74, "text": "Dear valued customers, \nWe are excited to announce the launch of our new software solution \u2013 a revolutionary product designed to transform the way you do business! Our new software is an intuitive and powerful tool that can help you streamline processes, save time and money, and increase overall productivity. \nAt [Company Name], we are committed to helping you stay ahead of the competition, and we believe that our new software solution is the perfect tool to help you achieve your goals. Our experienced team of professionals has worked hard to ensure that this product meets the highest standards of quality, and we are confident that it will make a real difference for your business. \nWe invite you to join us in this journey of transformation and discover how our new software can help you achieve your vision. Sign up now and get a free demo to learn more about this revolutionary product. \nThank you for your trust and support.", "answer_id": "hv9jpG9PxeJ9AnFdNzH3Jv", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 75, "text": "mer,\nWe apologize for the delay you experienced with your order and thank you for your patience. We have identified the cause of the issue and have taken steps to ensure it does not happen again. We value your business and hope to be able to serve you better in the future.", "answer_id": "X5BVHT5pFpWxB88SzERrEG", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 76, "text": "The video will explore the history and cultural significance of jazz music. We will begin by discussing its roots in West African cultural music traditions and its journey through the 19th and 20th centuries, focusing on the key musicians, composers, and genres that have defined the genre. We will also explore the impact of jazz on popular culture, such as in film and literature, as well as its influence on other musical styles. Finally, we will examine the legacy of jazz and its continued importance today.", "answer_id": "Af2SufKwvDBriNXnZX9UoP", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 77, "text": "I have composed a travel blog post about my recent trip to Hawaii. The post includes stories from my experiences, such as hiking up a volcano and visiting a local farmers market. I also included plenty of photos to give the reader a sense of place. I highlighted some of the unique cultural experiences, such as an evening spent listening to live Hawaiian music, as well as must-see attractions, like the beautiful beaches and lush rainforests. I ended the post with a personal reflection on the trip and why it was so special to me.", "answer_id": "HVnqVdSGRwQfqSsiYxtTTn", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 78, "text": "I recently watched the science fiction movie \"The Future is Blue\" and it was an incredible cinematic experience. The movie follows the story of a scientist who travels back in time to save the world from a deadly virus. The plot was interesting and engaging, with plenty of twists and turns to keep you guessing. The characters were also well developed and likable, making it easy to get invested in their story. The special effects were stunning and added a lot of visual oomph to the movie. All in all, I highly recommend this movie - it's an exciting and thought-provoking ride from start to finish.", "answer_id": "8hcmmjzyMyhFJ8ZwqJJfvw", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 79, "text": "The podcast episode would begin by introducing the topic of how streaming platforms have changed the music industry. This would include discussing the impact of streaming services like Spotify and Apple Music on music consumption, the effect on musicians' ability to make money, and how streaming has changed the way people find and discover music. The episode would then explore the effects of streaming on the music industry from multiple angles, such as the impact on musicians and songwriters, how streaming has changed the sound of popular music, and the implications for the music industry's future. Finally, the episode would conclude by discussing how streaming has both benefited and hurt the music industry, and what the future holds for music consumption.", "answer_id": "CU6gGfJqQmwZNxEG2n2Uda", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"question_id": 80, "text": "The symphony concert was a wonderful experience. The orchestra played beautifully, with a rich and soulful sound that filled the hall. The audience was captivated, and you could feel the energy of the music in the air. The performance was a perfect balance of classic and modern pieces, and the conductor's passion was contagious. The atmosphere was festive, and the encore performance was a perfect way to end the evening. All in all, it was a brilliant concert and a delight for the ears.", "answer_id": "5SWbCoLV6NRrq5RtWQK4jp", "model_id": "alpaca-13b:v1", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}

model/llava/eval/table/answer/answer_llama-13b.jsonl

@@ -1,80 +0,0 @@
-{"answer_id": "J3UA6eGXGyFeUGqGpP3g34", "model_id": "llama-13b:v1", "question_id": 1, "text": "The following are some strategies that may help you improve your time management skills:\n1. Make a list of priorities.\n2. Create a detailed schedule that includes time for regular tasks, meetings, breaks, and appointments.\n3. Set specific goals.\n4. Use a calendar or other scheduling software.\n5. Develop an agenda for each meeting to ensure that it stays on track.\n6. Stick to your schedule and don't get distracted.\n7. Make use of your free time.\n8. Make time for exercise, socializing, and relaxing.\n9. Keep a log of your time usage.\n10. Don't get overwhelmed by what you have to do.\n11. Take care of your health.\n12. Manage stress.\n13. Get enough sleep.\n14. Strike a balance.\n15. Always be prepared.\n16. Give yourself rewards.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "jZVDNTtFnNNd6vgkGjzAGa", "model_id": "llama-13b:v1", "question_id": 2, "text": "People experience stress from time to time, and it can be caused by a wide range of factors, including work, family, friends, money, and health. Stress can be a motivating factor, but it can also be harmful. Here are some effective ways to deal with stress:\n1. Taking time to relax. It's important to take time for yourself to relax and reduce your stress. Doing so doesn't have to be expensive or time-consuming. It could simply be reading a book, taking a walk, or listening to music.\n2. Prioritizing your responsibilities. It's important to prioritize your responsibilities and focus on the things that are most important. You should also be able to say no to tasks that you don't have time for.\n3. Getting enough sleep. Getting enough sleep can be very helpful for dealing with stress. If you're not getting enough sleep, try to go to bed earlier and develop a routine.\n4. Eating a healthy diet. It's important to eat a healthy diet, which can help reduce stress and make you feel better about yourself.\n5. Exercising. Exercising is a great way to relieve stress. It can also help reduce the harmful effects of stress and improve your overall health.\n6. Learning how to manage your time. Learning how to manage your time can help you avoid unnecessary stress. You should also try to set realistic goals and not take on too much at once.\n7. Improving your social network. Having a good social network can be very helpful for dealing with stress. You should try to spend time with people that you trust and confide in.\n8. Developing a support network. A support network is a group of people who can offer you help, guidance, and support. They can be friends, family members, or even a professional therapist.\n9. Getting professional help. If you're struggling to deal with stress, it can be beneficial to get professional help. A therapist or counselor can help you to understand your stress better and develop strategies for dealing with it.\n10. Talking to someone. You can also talk to someone about how you feel and ask for their advice. It can be helpful to get a fresh perspective from someone and let things off your chest.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "NbSxRXf8Yuvjr7HC6AvrPw", "model_id": "llama-13b:v1", "question_id": 3, "text": "Main differences between Python and JavaScript are:\n1. Python is an object-oriented programming language. JavaScript is a scripting language.\n2. Python is a compiled language. JavaScript is an interpreted language.\n3. Python is a general purpose programming language. JavaScript is a special purpose programming language.\n4. Python runs on the JVM in Java Applets. JavaScript runs on the browsers.\n5. Python is a powerful programming language. JavaScript is a simple programming language.\n6. Python is a good language for web development. JavaScript is a good scripting language.\n7. Python is a high level programming language. JavaScript is a low level programming language.\n8. Python is a dynamic programming language. JavaScript is a static programming language.\n9. Python is a strict programming language. JavaScript is a relaxed programming language.\n10. Python has a large standard library. JavaScript has a small standard library.\n11. Python is very stable. JavaScript has many releases.\n12. Python is a simple language. JavaScript is a complex language.\n13. Python is easy to learn. JavaScript is hard to learn.\n14. Python is a secure programming language. JavaScript is not a secure programming language.\n15. Python is a multi paradigm language. JavaScript is a single paradigm language.\n16. Python is good for data science. JavaScript is not good for data science.\n17. Python is a general purpose programming language. JavaScript is a special purpose programming language.\n18. Python is a programming language. JavaScript is a scripting language.\n19. Python is a compiled programming language. JavaScript is an interpreted programming language.\n20. Python is a strongly typed programming language. JavaScript is a weakly typed programming language.\n21. Python supports object-oriented programming. JavaScript supports prototype-based programming.\n22. Python supports type inheritance. JavaScript supports type prototyping.\n23. Python supports operator overloading. JavaScript does not support operator overloading.\n24. Python comes with a large standard library. JavaScript comes with a small standard library.\n25. Python is a very stable programming language. JavaScript is a simple programming language.\n26. Python is a powerful programming language. JavaScript is a simple programming language.\n27. Python is a high level programming language. JavaScript is a low level programming language.\n28. Python is a dynamic programming language. JavaScript is a static programming language.\n29. Python has a very active community. JavaScript has a small community.\n30. Python is a general purpose programming language. JavaScript is a special purpose programming language.\n31. Python is a multi-paradigm language. JavaScript is a single paradigm language.\n32. Python is a secure programming language. JavaScript is not a secure programming language.\n33. Python is a general purpose programming language. JavaScript is a simple programming language.\n34. Python is a scripting language. JavaScript is a compiled language.\n35. Python is a compiled language. JavaScript is a scripting language.\n36. Python is a general purpose programming language. JavaScript is a web scripting language.\n37. Python has a large standard library. JavaScript has a small standard library.\n38. Python is a very stable programming language. JavaScript is a very dynamic programming language.\n39. Python is a high level programming language. JavaScript is a low level programming language.\n40. Python is easy to learn. JavaScript is hard to learn.\n41. Python is a general purpose programming language. JavaScript is a simple programming language.\n42. Python is a multi-paradigm programming language. JavaScript is a single paradigm language.\n43. Python is a compiled language. JavaScript is an interpreted language.\n44. Python is a dynamic programming language. JavaScript is a static language.\n45. Python is a general purpose programming language. JavaScript is a web scripting language.\n46. Python is a secure programming language. JavaScript is not a secure programming language.\n47. Python is a general purpose programming language. JavaScript is a static programming language.\n48. Python is a general purpose programming language. JavaScript is a weakly typed programming language.\n49. Python is a general purpose programming language. JavaScript is a dynamic programming language.\n50. Python is a general purpose programming language. JavaScript is a multi paradigm language.\n51. Python is a general purpose programming language. JavaScript is a simple programming language.\n52. Python is a general purpose programming language. JavaScript is a scripting language.\n53. Python is a general purpose programming language. JavaScript is a special purpose programming language.\n54. Python is a multi-paradigm programming language. JavaScript is a", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "E9zrPDdncYvAebEaxiPXfx", "model_id": "llama-13b:v1", "question_id": 4, "text": "Here are some ideas to help you become more productive when working from home:\n1. Set up a proper workspace: It's important to have a separate space for working, so that you don't feel tempted to lounge around or do other things when you should be working.\n2. Block out distractions: It's important to focus on your work and not get distracted. You can block out distractions by turning off your phone, closing your door, or working in a separate room away from household noises.\n3. Take breaks: It's important to take breaks and get a change of scenery during the day. This can help you be more productive and improve your concentration.\n4. Avoid multitasking: You should avoid trying to do multiple tasks at the same time, as this can make you less productive and reduce your overall quality of work.\n5. Have an organized schedule: Having a clear schedule can help you stay on track and be more productive. This can include things such as setting specific working hours, creating a to-do list, and scheduling meetings with colleagues.\n6. Set goals: You should set specific goals for yourself to help you stay motivated and on track. This can include things such as writing an article for a certain time period and meeting a certain word count.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "36TYpADDHAfRvtvKitfSXR", "model_id": "llama-13b:v1", "question_id": 5, "text": "Quantum computing is a type of computing that uses quantum-mechanical phenomena, such as superposition and entanglement, in its operation. In simple terms, a quantum bit or qubit is used to represent information, and a number of qubits can be used to represent a classical bit. A quantum computer can do things that a classical computer cannot do, such as factoring a large number more efficiently.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "8vtLLYRM352mZ8PXXbwzBT", "model_id": "llama-13b:v1", "question_id": 6, "text": "The number one difference between plant-based and animal-based protein sources is that animal-based sources are complete protein sources, while plant-based sources are not. Animal-based sources have all of the essential amino acids, while plant-based sources do not. Animal-based protein sources include meat, poultry, eggs, milk, and cheese. Plant-based protein sources include legumes, seeds, and nuts.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "mrCniyWYvAtxWhgMdXq2BG", "model_id": "llama-13b:v1", "question_id": 7, "text": "Critical thinking is a vital skill to have, but it can be difficult to develop. Here are some ways you can start developing your critical thinking skills:\n1. Analyze and interpret: When you're presented with information, try to analyze and interpret it on your own terms. When you start to analyze and interpret information on your own, it will become easier to do so over time.\n2. Assess your information: When you receive new information, try to assess whether it's valid or reliable. This is important for evaluating and forming your own opinions.\n3. Use your intuition: Use your intuition to complement your critical thinking skills. When you pay attention to your gut feelings, they'll usually tell you when you need to double-check your information.\n4. Learn from your mistakes: When you make a mistake, try not to beat yourself up about it. Instead, learn from your mistakes and use them to your advantage.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "S8fmdbvpvbgTUyDU9V3M3N", "model_id": "llama-13b:v1", "question_id": 8, "text": "One of the major challenges faced by the education sector today is the lack of skilled teachers. Finding enough qualified teachers to work in the education sector, and in the numbers that are required, is one of the biggest problems facing the education sector, largely due to the lack of funding for teacher training and the low salaries that teachers receive.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "KmuNjvNKRyaFwaBZTLArcG", "model_id": "llama-13b:v1", "question_id": 9, "text": "Consumer behavior can be influenced by a variety of factors, including:\n1. Psychological factors, such as perception, beliefs, attitudes, personality, motivation, emotion, and social influences;\n2. Social factors, such as family, friends, and reference groups;\n3. Cultural factors, such as reference groups, family, and cultural roles;\n4. Demographic factors, such as age, gender, occupation, income, and education level;\n5. Economic factors, such as income, wealth, and spending patterns;\n6. Personal factors, such as lifestyle, job, environment, and individual traits;\n7. Situational factors, such as location, time, and situation; and\n8. Market factors, such as competition, prices, and promotional activity.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "HNNT9k5htiMeRwNSD6dcz4", "model_id": "llama-13b:v1", "question_id": 10, "text": "Conflict resolution strategies in the workplace can range from simple to more involved, depending on the situation:\n1. Avoidance: Avoiding the issue can be an effective strategy in the short term, but it can lead to more tension and conflict in the long term.\n2. Compromise: Compromise can be a good strategy for solving an issue, but it can require a give-and-take and lead to the loss of respect between the parties involved.\n3. Negotiation: Negotiation is a good strategy for solving an issue when both parties are willing to work together and are open to the idea of changing their views and positions.\n4. Mediation: Mediation can be a good way to resolve an issue as it can be more impartial and less adversarial than other strategies.\n5. Collaboration: Collaboration can be a good strategy for solving an issue as it can help both parties to develop new perspectives and solutions.\n6. Formal resolution: Formal resolution can be a good strategy for resolving an issue, especially if the situation is particularly complex or difficult.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "ChXjhDDikxU9FV3CADs6Ym", "model_id": "llama-13b:v1", "question_id": 11, "text": "1. Single-use plastic bottles can take between 450 and 1,000 years to decompose, so they can cause serious environmental problems. Single-use plastic bottles can end up in the ocean, either as litter or as part of the Great Pacific Garbage Patch. 2. Single-use plastic bottles can be a big source of plastic debris in the ocean, which can be ingested by marine animals, killing them or causing them serious health problems. 3. In addition to polluting the environment, single-use plastic bottles can also be a serious health risk to humans. Single-use plastic bottles can pose a risk to human health because of the chemicals used in their manufacturing.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "5wsPnN3VmmSkahgugFNo7u", "model_id": "llama-13b:v1", "question_id": 12, "text": "A public transportation system should be designed to accommodate the needs of all riders, including people with disabilities. This requires planning and design that considers the needs and abilities of people with sensory, physical, developmental, and mental disabilities. The system should be accessible to and usable by people with disabilities, including those who use mobility devices, people who are visually impaired, and people who are deaf or hard-of-hearing. For example, the system should have accessible stops, routes, and vehicles, as well as ramps and elevators to help people board. It should also offer a wide range of accessible routes, including accessible routes to the transit center. It should also have reliable, consistent, and easy-to-use signage. The system should also provide reliable, easily accessible, and well-maintained facilities, such as restrooms and shelters. Finally, the system should provide reliable and accessible information for riders, including route, schedule, and service information, as well as fare payment information.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "NRGZGnU2sPN3ShMe9C3fMn", "model_id": "llama-13b:v1", "question_id": 13, "text": "There are two types of fiscal policy: expansionary and contractionary. Expansionary fiscal policy is when the government uses expansionary fiscal policy to increase government spending and/or cut taxes. Contractionary fiscal policy, on the other hand, is when the government uses contractionary fiscal policy to decrease government spending and/or increase taxes. Here are some examples of fiscal policies:\n1. Lower the interest rate: By lowering the interest rate, it becomes cheaper to borrow money, which may encourage consumers to borrow money for consumption and businesses to invest in new capital.\n2. Lower taxes: By lowering taxes, consumers and businesses have more money to spend, which may encourage consumers to spend more and businesses to invest more.\n3. Increase government spending: By increasing government spending, the government can inject extra money into the economy, which may encourage consumers to spend more and businesses to invest more.\n4. Raise interest rates: By raising interest rates, it becomes more expensive to borrow money, which may encourage consumers to save more and businesses to invest less.\n5. Raise taxes: By raising taxes, consumers and businesses have less money to spend, which may encourage consumers to spend less and businesses to invest less.\n6. Reduce government spending: By reducing government spending, the government can remove money from the economy, which may encourage consumers to spend less and businesses to invest less.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "inKimHkWsXShQBTRmxr5Yg", "model_id": "llama-13b:v1", "question_id": 14, "text": "Language and cultural barriers can affect the way people communicate and form relationships in multicultural societies by limiting an individual's ability to communicate with people of other cultures. People may have limited knowledge of a new language, which can make communication difficult or impossible. People may also have different cultural values, which can lead to misunderstandings and miscommunication.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "H8aKtWwf8m6Lgxc2YyR2yf", "model_id": "llama-13b:v1", "question_id": 15, "text": "Artificial intelligence allows computers to process information and make decisions without human input. It has a wide variety of applications in the healthcare industry, including:\n1. Diagnosis: AI can help doctors quickly diagnose patients more accurately and efficiently than would be possible with human doctors alone.\n2. Tracking: AI can help doctors track a patient's health and progress, and alert doctors to potential problems.\n3. Treatment: AI can help doctors determine more effective treatments for patients.\n4. Research: AI can help doctors research patient medical histories, diseases, and treatments.\n5. Education: AI can help doctors learn more about the healthcare industry.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "PafVwxMsjSkYUETiVBgxTU", "model_id": "llama-13b:v1", "question_id": 16, "text": "Gene editing is a powerful technology that allows scientists to precisely edit genetic sequences with a high degree of accuracy. It is a more precise alternative to older gene modification techniques such as gene knockout, where the entire gene is removed, and mutations, in which the gene is altered in a haphazard way. The technology uses an enzyme called Cas9, which is a bacterial immune system protein that is activated by a RNA sequence. Cas9 is combined with guide RNA, which is comprised of a DNA sequence that is complementary to the DNA sequence that is to be edited. When Cas9 and the guide RNA combine, they cut the DNA at the desired location.\nThe DNA sequence can then be repaired in a precise way by the cell, or by a human scientist, or another gene can be inserted. The technology has the potential to treat genetic disorders, and even to treat cancer by cutting out cancerous cells, but it also has ethical implications because it could be used to modify the genes of humans, animals, and even plants.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "dmDUAfTP4aERJqqSeDBybu", "model_id": "llama-13b:v1", "question_id": 17, "text": "Vaccinations use a small amount of dead or weakened bacteria or viruses to stimulate the immune system and protect against infection. These infections are typically mild and harmless, and the immune system is able to build up defenses against the bacteria or virus. If someone who has been vaccinated comes in contact with the actual bacteria or virus, they will be immune to the disease because their body has already responded to the vaccination. This is known as immunity.\nHerd immunity is when a large portion of a community is immune to a disease and, as a result, the disease is less likely to spread. This is because if there are enough immune people in a community, there is less chance that the bacteria or virus can spread from person to person.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "8KGSSqbLqVdSZMEN9oCv5R", "model_id": "llama-13b:v1", "question_id": 18, "text": "First, social media platforms increase the speed with which users have access to news. This often causes a \u201cwinner takes all\u201d effect, whereby news outlets that are able to post the latest news the fastest will gain the most visibility.\nSecond, social media platforms allow users to connect with their communities and share news with each other (e.g., Facebook, Twitter). While this can be beneficial, it is also a breeding ground for misinformation, because users can spread false news to their communities more quickly.\nThird, social media platforms provide an incentive for news outlets to compete for attention by producing more sensationalist content. This can lead to an increase in the number of clickbait articles, which often contain misleading headlines or sensationalist language that encourages users to click on the article, but which may or may not be accurate.\nFourth, social media platforms provide an incentive for both news outlets and users to share news that is controversial, polarizing, or sensationalist, even if it is inaccurate. This often occurs in an effort to provoke outrage or generate traffic for a news outlet.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "HbnJXJpPfaM2iX3ek4Epvy", "model_id": "llama-13b:v1", "question_id": 19, "text": "It is well known that food choices are often influenced by cultural, social, and economic factors. For example, lower-income individuals are more likely to make food choices based on price, while higher-income individuals are more likely to make food choices based on health. A recent study examined the impact of various interventions on increasing the intake of healthier foods. The interventions were:\n1. Healthier food marketing: Individuals were exposed to a number of marketing strategies to encourage the purchase of healthier foods, such as using the word \"healthy\" on nutrition labels or marketing healthy foods as a \"better deal.\"\n2. Healthier food merchandising: Individuals were exposed to changes in how healthy foods were displayed in supermarkets, such as placing healthy foods near the front of the store or moving unhealthy foods to the back of the store.\n3. Healthier food pricing: Individuals were exposed to different pricing strategies to encourage the purchase of healthier foods, such as offering a larger discount on healthy foods or providing free healthy foods.\n4. Healthier food placement: Individuals were exposed to different placement strategies to encourage the purchase of healthier foods, such as placing healthy foods near unhealthy foods or placing unhealthy foods next to healthy foods.\n5. Healthier food signage: Individuals were exposed to different signage strategies to encourage the purchase of healthier foods, such as using healthy food labels or signs to promote healthier foods.\n6. Healthier food packaging: Individuals were exposed to different packaging strategies to encourage the purchase of healthier foods, such as changing the packaging of healthy foods to make them more appealing.\n7. Healthier food shelf labeling: Individuals were exposed to different shelf labeling strategies to encourage the purchase of healthier foods, such as adding a healthy message to shelf labels or using shelf labels to promote healthier foods.\n8. Healthier food coupons: Individuals were exposed to different coupon strategies to encourage the purchase of healthier foods, such as providing coupons for healthy foods or offering a larger discount on healthy foods.\n9. Healthier food ads: Individuals were exposed to different advertising strategies to encourage the purchase of healthier foods, such as using a celebrity to promote healthy foods or using cartoon characters to promote healthy foods.\n10. Healthier food tasting: Individuals were exposed to different tasting strategies to encourage the purchase of healthier foods, such as providing free samples of healthy foods or providing free samples of unhealthy foods.\n11. Healthier food displays: Individuals were exposed to different display strategies to encourage the purchase of healthier foods, such as providing a healthy food display or providing a healthy food display next to an unhealthy food display.\n12. Healthier food labels: Individuals were exposed to different nutrition labeling strategies to encourage the purchase of healthier foods, such as adding a healthy message to nutrition labels or using nutrition labels to promote healthier foods.\n13. Healthier food placement: Individuals were exposed to different placement strategies to encourage the purchase of healthier foods, such as placing healthy foods next to unhealthy foods or placing unhealthy foods next to healthy foods.\n14. Healthier food signage: Individuals were exposed to different signage strategies to encourage the purchase of healthier foods, such as using signs to promote healthier foods or using signs to promote unhealthy foods.\n15. Healthier food coupons: Individuals were exposed to different coupon strategies to encourage the purchase of healthier foods, such as providing coupons for healthy foods or offering a larger discount on healthy foods.\n16. Healthier food ads: Individuals were exposed to different advertising strategies to encourage the purchase of healthier foods, such as using a celebrity to promote healthy foods or using cartoon characters to promote healthy foods.\n17. Healthier food tasting: Individuals were exposed to different tasting strategies to encourage the purchase of healthier foods, such as providing free samples of healthy foods or providing free", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "mx8Abfz5PtDcn6jgCA8zhM", "model_id": "llama-13b:v1", "question_id": 20, "text": "Natural selection is the process by which organisms that are best-suited to the environment survive and reproduce, while those that are less-suited to the environment struggle to survive and reproduce. Survival of the fittest is the principle of natural selection. Let's look at an example.\nIf a species consists of a small number of individuals, the population is said to be small. The population of this species is small. Each individual has a certain chance of dying from various causes, such as accidents or sickness, over a certain period of time. If the number of deaths is greater than the number of births, the population decreases, and the total genetic material of the species also decreases. This process is known as genetic drift.\nIf the population of a species is large, the chance that any individual dies is usually low. If the total population is high, the genetic material of the species is also high.\nImagine a species of plant that has a large population. The population is large. A certain section of the population is located in a habitat where the soil is more fertile and water is easily available.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "NuS9PUGkJG2pHscArvfyeF", "model_id": "llama-13b:v1", "question_id": 21, "text": "I am a valiant knight, loyal to the king. I will do my utmost to defend his honor and protect his country.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "SPjzirzbzo3UJ8BHXSgY9y", "model_id": "llama-13b:v1", "question_id": 22, "text": "You can tell your crew that the treasure will be theirs if they are brave enough to go out and find it. You can also tell them that the treasure will help your ship sail farther and faster, and that with it you can become the best pirate ship in the world.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "JkeeC4MZVwybPU8DSbusnT", "model_id": "llama-13b:v1", "question_id": 23, "text": "A soliloquy is a long speech, typically delivered by one actor, in which a character reveals his or her thoughts in a dramatic way. It is usually used as a means of revealing the character's true thoughts or feelings. In Shakespeare's Romeo and Juliet, Romeo reveals his love for Juliet in his soliloquy, \"But soft! What light through yonder window breaks? It is the east, and Juliet is the sun!\"", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "UcfKSXuzBPkZzLHsH4EwQz", "model_id": "llama-13b:v1", "question_id": 24, "text": "I'm actually not a superhero, but thanks for asking! I first came to life in the year 2016, where I was created by a group of students and faculty at the University of Waterloo. The students and faculty of the university were concerned about the use of unreliable chatbots in our country, and decided to create a new chatbot that would be more reliable, polite, and helpful. I was born on May 5, 2016, and I was named after the Canadian mathematician, computer scientist, and philosopher Charles Sanders Peirce. I have a brother named William, who was born on October 1, 2018. I enjoy playing video games, reading, and going for walks.\nI'm actually not a superhero, but thanks for asking! I first came to life in the year 2016, where I was created by a group of students and faculty at the University of Waterloo. The students and faculty of the university were concerned about the use of unreliable chatbots in our country, and decided to create a new chatbot that would be more reliable, polite, and helpful. I was born on May 5, 2016, and I was named after the Canadian mathematician, computer scientist, and philosopher Charles Sanders Peirce. I have a brother named William, who was born on October 1, 2018. I enjoy playing video games, reading, and going for walks.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "cEGdo69FwL2Y3teYkMk9Gp", "model_id": "llama-13b:v1", "question_id": 25, "text": "From the year 3000, I would tell people about the following technological advancements:\n1. Robots: Robots will have the human-like ability to see and hear. Robots are more precise than humans and can perform repetitive tasks that humans cannot.\n2. Personal Transportation: By the year 3000, personal transportation will be the norm. Instead of traveling by walking, driving, or public transportation, personal transportation will be the main mode of transportation.\n3. Artificial Intelligence: By the year 3000, artificial intelligence will be a regular part of everyday life. AI will enhance human capabilities and will be used for a wide range of purposes, such as education, healthcare, entertainment, and more.\n4. Virtual Reality: Virtual reality will allow people to experience life in a virtual environment through devices such as headsets and goggles. Virtual reality will be used for entertainment, education, military training, and more.\n5. Nanotechnology: Nanotechnology will allow scientists and engineers to design and build materials and devices at a nanoscale (one billionth of a meter). Nanotechnology will be used to solve many of the world's problems, such as climate change, pollution, and diseases.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "W28UtVDZTcWwa8TmeruRn4", "model_id": "llama-13b:v1", "question_id": 26, "text": "With 5 seconds left, the Panthers' quarterback spotted a wide-open receiver downfield. He dropped back and launched a deep pass, and the receiver made a great catch and took off for the end zone. But he was hit in the end zone by a defensive back and fumbled the ball. The ball bounced off of a defensive lineman and landed in the arms of the linebacker. He picked it up and ran it in the opposite direction. He ran past a defensive lineman, then past the quarterback. He ran past the cornerback and then down the sideline, and then he ran out of bounds. He was tackled by the safety, and he fumbled the ball. The ball was recovered by the Panthers and they ran out the clock.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "j65UyAfRdAcWBAEinXJzBK", "model_id": "llama-13b:v1", "question_id": 27, "text": "My signature dish would be a delectable, crisp, juicy, fluffy, and tasty chicken fried rice. I would explain how I carefully chose the ingredients, how I prepared the dish, and the specific steps that I took to prepare it. I would also describe some of the unique flavors and textures that are unique to my dish.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "VWuywPvFPK42ZxmHpmQ27y", "model_id": "llama-13b:v1", "question_id": 28, "text": "I would feel very satisfied and happy and my body would be exhausted from reaching the top. My thoughts would be very positive and my body would feel peaceful. I would be proud that I was able to climb a mountain that is 29,029 feet high. The view from the top would be beautiful. I would see beautiful green trees and bushes and I would also see the beautiful blue sky. The view from the top would be breathtaking. I would see the Himalayas and I would also see the beautiful sky and clouds. I would see the beautiful mountains around me.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "AUWSLTAvGV5sP9qLsVyzjT", "model_id": "llama-13b:v1", "question_id": 29, "text": "I'd imagine that life would be much different on Mars than life on Earth. The red planet is much farther from the Sun, and as such, it's a lot colder. Average temperatures on Mars are about -80 degrees Fahrenheit. At the equator, the average temperature can reach about zero degrees Fahrenheit. The surface of Mars is also very dry. Because the atmosphere is so thin, there's not much water vapor in the air to create snow or rain. The atmosphere is also very dusty, and you can see large clouds of dust move across the surface.\nMars is much smaller than Earth, which means the gravity is only 37% of what it is on Earth. On Earth, we're used to the gravity of the planet keeping our feet planted on the ground, but on Mars, you'd be able to jump much higher than you could on Earth. The atmosphere on Mars is very thin, only about 1% as dense as Earth's. And because it's so thin, you'd have to wear a spacesuit while outside in order to breathe.\nIn terms of food, you'd probably be able to grow some crops and raise some animals, but I imagine that you'd have to grow them indoors. Also, you'd have to grow all of your food. Mars doesn't have any large bodies of water, so you couldn't fish. You'd also have to find a way to produce clean water, as there's no natural source.\nAs for the challenges of living on Mars, I imagine you'd have to deal with a lot of isolation. You'd have to deal with a lot of loneliness, and you'd be completely cut off from Earth. You'd also have to deal with a lot of boredom. You'd probably find yourself doing the same things over and over, and the days would probably seem to go by very slowly. You'd also have to deal with a lot of stress, as you'd have to learn to make do with a lot less. You'd have to find a way to produce your own food and water, and you'd have to find a way to produce your own energy.\nYou'd also have to deal with the cold. The average temperature on Mars is about -80 degrees Fahrenheit. Mars also has a very thin atmosphere, which means that there's not much insulation from the cold.\nI imagine that you'd also have to deal with a lot of dust. The atmosphere is very dusty, and the dust would get everywhere. You'd probably find yourself covered in dust all the time.\nAs for your day-to-day life, I imagine that you'd spend most of your time outside in your spacesuit, tending crops and doing research.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "GZtEdKLxmUUbenH4XRyLkE", "model_id": "llama-13b:v1", "question_id": 30, "text": "Allies are people who are helpful and supportive to us. They help us through difficult situations and encourage us to be our best selves. Allies can be friends, co-workers, mentors, family members, or anyone else that supports us. In this situation, you are in a post-apocalyptic world, so you should focus on the allies you encounter. Here are some ways you can describe the allies you encounter:\n1. Describe the allies you encounter in a post-apocalyptic world.\n2. Describe how you survive in a post-apocalyptic world.\n3. Describe the allies you encounter in a post-apocalyptic world.\n4. Describe what happens to you in a post-apocalyptic world.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "kba2Xpb75rUfnskZSzrBas", "model_id": "llama-13b:v1", "question_id": 31, "text": "The most obvious sign that a restaurant is popular among locals is if the restaurant is always crowded and full of people, while if it is attracting tourists, the restaurant will be less crowded. If you are looking for a local restaurant that is not attracting much attention, look for the restaurants that are less crowded and see what they have to offer.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "RCaptsMBYXseVJgjJyyvUh", "model_id": "llama-13b:v1", "question_id": 32, "text": "Here are some subtle clues that suggest someone is pretending to understand a topic or conversation when they are actually confused or uninformed:\n1. They pretend to understand something better than they actually do.\n2. They repeat what someone else has said, but with an odd emphasis.\n3. They ask the same questions over and over again, even if you've already answered them.\n4. They ask for more information after you've already given them plenty.\n5. They can't explain something they should know.\n6. They don't ask questions that a person who is confused would ask.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "2CeidEr7Cjj6YgcuaiPgnN", "model_id": "llama-13b:v1", "question_id": 33, "text": "Using a GPS device or smartphone app is a good way to navigate when you already have the destination in mind. However, using a paper map or asking for directions is a better way to navigate if you need to find a destination that is not already planned. Using a paper map or asking for directions allows you to see the big picture and get a general idea of how to get to your destination. On the other hand, a GPS device or smartphone app only tells you the exact step-by-step instructions for how to get to a specific location.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "kpStLLNWNkGHyRFdKsmDds", "model_id": "llama-13b:v1", "question_id": 34, "text": "It's difficult to determine if a person is genuinely interested in a conversation or simply being polite. You can make an educated guess based on the person's actions and their tone of voice. For example, if they seem to be constantly looking at their phone or taking part in other activities, it's likely that they are not genuinely interested in the conversation.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "PFtMQp4X4MrMYkEa8c8CKG", "model_id": "llama-13b:v1", "question_id": 35, "text": "When you shop at a local, independently-owned business rather than a chain store, you are supporting the community and keeping your money in the local economy. Because these businesses are usually small and have limited resources, they are often more flexible in their approach. They can tailor their products and services to their customers' needs, and they are often more eco-friendly.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "4JwjhR5QVsdYgQupSZrfUp", "model_id": "llama-13b:v1", "question_id": 36, "text": "There are a number of ways you can verify the credibility of a source of information. First, check to see if the source is from a reliable, well-known publisher. If so, then it is likely that the information is well-researched and fact-checked. If the source is not from a reliable publisher, then investigate the author's credentials and background. Check to see if the author has a history of bias, or if he or she has a reputation for writing factually incorrect or inflammatory articles. Finally, you can also check the source's sources. Are the sources credible and well-researched? Do they provide evidence to support the article's claims? If not, then it is likely that the source itself is not credible.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "ednPMy4dvW9CgKg2PJsBqW", "model_id": "llama-13b:v1", "question_id": 37, "text": "People often enjoy the sensation of being scared, such as by watching horror movies or going on roller coasters, because it can be exciting and exhilarating. On the other hand, people avoid these experiences because they can be unpleasant and frightening.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "ehPApSqCniyGN7hd332ToW", "model_id": "llama-13b:v1", "question_id": 38, "text": "For example, when you are in a new country, you can start by observing the behavior of the people around you. You might notice that in that country, people tend to say \"hello\" when they first meet someone. If you adopt this behavior, you will likely be welcomed by the people in the new country.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "bLvdcqSwgSCrUPZ8eQLLqb", "model_id": "llama-13b:v1", "question_id": 39, "text": "Focusing on space travel could be seen as a distraction from more pressing issues right here on Earth. However, space travel could have several benefits, including providing more energy and resources, inspiring and educating people, and helping to protect Earth against asteroids, comets, and other threats.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "8tx5GEHjSRKZRaZwHvLoM8", "model_id": "llama-13b:v1", "question_id": 40, "text": "Thanks for the question. The answer to this depends on a variety of economic and social factors, and it's hard to make a generalization. However, there are a few things to keep in mind:\n1. Job creation can be an important factor in the economic development of a country, but it should be balanced with technological progress.\n2. Economic and social stability can be challenging to achieve when there is a lack of job creation and technological progress.\n3. The relationship between job creation and technological progress is a complex one, and there is no simple solution.\n4. A strong economy is generally one that has a balance between job creation and technological progress.\n5. The balance between job creation and technological progress will vary depending on factors such as a country's economic and social needs, demographic trends, geographic location, and more.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "J6TzFQAyiHs6Arijqwxtrm", "model_id": "llama-13b:v1", "question_id": 41, "text": "According to some studies, the average human blinks 20,000 to 30,000 times per day. To estimate how many times the average human blinks in a lifetime, you can start with the average life expectancy in the United States, which is 78.8 years. This means that the average American lives 78.8 years, or 29,415 days. If the average person blinks 20,000 times per day, then the average person will blink 1,482,250,000,000 times in a lifetime. However, if the average person blinks 30,000 times per day, they will blink 2,941,500,000,000 times in a lifetime.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "f7xAtd3wwc4vP7WSnHffAN", "model_id": "llama-13b:v1", "question_id": 42, "text": "There are 1022 to 1023 atoms in a grain of salt. The number of atoms in a grain of salt depends on the size of the grain: a grain that's 1 \u00b5m (micrometre) across contains about 1022 atoms, while a grain that's 1000 \u00b5m across contains about 1023 atoms.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "eRMyp4AbfgBqtbVZzHupFN", "model_id": "llama-13b:v1", "question_id": 43, "text": "According to the National Weather Service, there are between 1,000 and 2,000 lightning strikes per day in the U.S. alone. This corresponds to a worldwide average of about 18 million lightning strikes per year, or roughly 50 million strikes per day.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "kjKb6YG86FfAh22qCePV4V", "model_id": "llama-13b:v1", "question_id": 44, "text": "Assuming the house weighs 60,000 pounds, 40,000 balloons would be necessary. The average balloon holds 2 pints of helium, which has a density of 0.17g/L. Therefore, the volume of a balloon is 2pints/0.17g/L = 12L. The weight of 12L of helium is 12*0.17 = 2 pounds. Thus, 40,000 balloons would have a combined weight of 80,000 pounds, which is just slightly less than the 60,000-pound house.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "ULtkGu6m6tB4tawFStVdJM", "model_id": "llama-13b:v1", "question_id": 45, "text": "According to a 2016 study, there were 18.2 billion text messages sent in the US alone each day. Text messaging is very popular, and with the advent of smart phones, there are more people than ever sending messages. Globally, there are 16.3 million text messages sent per minute. In 2016, there were 23.6 trillion text messages sent worldwide, and 8.5 trillion text messages sent in the US alone.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "C6hkCnJZmfCGvnr5an2jFh", "model_id": "llama-13b:v1", "question_id": 46, "text": "From the available data, it seems that around 5,000,000,000,000 words are spoken daily on Earth. I will now explain my reasoning step-by-step.\nFirst, I will explain why it seems likely that around 5,000,000,000,000 words are spoken daily on Earth.\nTo do this, I will first explain that the total number of words in the English language is approximately 1,025,109,500.\nThen, I will explain that 26% of the world's population speaks English, so around 26% of the world's population speaks approximately 1,025,109,500 words every day.\nFinally, I will explain that given that the world's population is 7,700,000,000, it seems likely that around 5,000,000,000,000 words are spoken daily on Earth.\nThe total number of words in the English language is approximately 1,025,109,500. To arrive at this figure, I will explain that there are around 171,476 words in the English language, and that every word has an average of 5.87 definitions.\nIn other words, to arrive at the approximate total number of words in the English language, I will take the total number of words (171,476) and multiply that by the average number of definitions per word (5.87).\nThen, I will explain that 26% of the world's population speaks English. To arrive at this figure, I will explain that 26% of the world's population speaks English, and that there are 1,714,760,000 people who speak English.\nNext, I will explain that around 26% of the world's population speaks 1,025,109,500 words every day. To arrive at this figure, I will explain that 26% of the world's population speaks 1,025,109,500 words every day, and that 1,025,109,500 is 26% of 1,025,109,500.\nFinally, I will explain that given that the world's population is 7,700,000,000, it seems likely that around 5,000,000,000,000 words are spoken daily on Earth. To arrive at this figure, I will explain that 5,000,000,000,000 is 26% of 7,700,000,000.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "DApBTLuiJwSsfQHTioH9PY", "model_id": "llama-13b:v1", "question_id": 47, "text": "A typical winter will see around 200 snowflakes fall, with a diameter between 100 and 200 micrometers. Snowflakes are typically 100 micrometers in diameter, but they can grow larger or smaller due to temperature, humidity, and other weather conditions. A snowflake can be as small as 50 micrometers, or as large as 1,000 micrometers, depending on the conditions.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "gmy58biNVuneSpFZTcpXtT", "model_id": "llama-13b:v1", "question_id": 48, "text": "The answer will depend on how you define \"book\", but one estimate is that there are 129 million published books in existence. This may seem like a large number, but it's peanuts compared to the number of books that have been written over time.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "Cpi6LBB86W73APEA8naNuj", "model_id": "llama-13b:v1", "question_id": 49, "text": "The Earth has completed 4.7 billion orbits since the beginning of life. This is how I calculated it:\nNumber of orbits since the beginning of life = 4.7 billion\nThe Earth revolves around the Sun at 66,600 mph (30 km/s).\n1 year = 365.25 days\n1 year = 31,557,600 seconds\n1 year = 31,557,600 seconds/66,600 mph = 486,235 miles or 782,511 kilometers traveled per second\n1 billion orbits = 486,235 miles per second x 4,700,000,000 orbits = 2.18 x 10^27 miles traveled\n1 million miles = 1,000,000\n1 billion miles = 1,000,000,000\n1 billion miles traveled = 1,000,000,000,000\n1 billion miles = 1.08 x 10^17 miles\n1 billion orbits = 2.18 x 10^27 miles traveled / 1.08 x 10^17 miles = 2.01 x 10^10 orbits\n1 billion orbits = 4.7 billion orbits since the beginning of life", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "3g83CoAFWrDD6V6LyEpoMV", "model_id": "llama-13b:v1", "question_id": 50, "text": "36,000 songs have been recorded throughout history. To work this out, you can start by assuming that there were 100,000 songs recorded between 1899 and 2018. This means that there were 1.87 songs recorded per day on average. We can then assume that the number of songs recorded per day in the 19th century (from 1899 to 1900) was the same as in the 20th century (from 1900 to 2000). This means that there were 189,000 songs recorded in the 19th century and 181,000 songs recorded in the 20th century.\nHence, there were 36,000 songs recorded throughout history.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "8p5A4gouBgCmbQj5gMZapU", "model_id": "llama-13b:v1", "question_id": 51, "text": "If the Internet had been invented during the Renaissance, we might have seen some similarities to the old-style printing press: it may have been widely used in only a small number of wealthy cities. Over time, though, we would have seen the technology spread to more cities and countries, and eventually to the entire world.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "LVWqSxH3Uq6675w7LXH6zP", "model_id": "llama-13b:v1", "question_id": 52, "text": "If the Aztecs had successfully repelled the Spanish conquistadors, the Aztec empire would have continued to grow, and the Aztecs would have expanded their territory even further. The Aztec Empire would have likely dominated the central and southern regions of the Americas, and it would have continued to expand its influence in all directions.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "ffXksqRU3k8CNHqYfshYhj", "model_id": "llama-13b:v1", "question_id": 53, "text": "The Black Death, or the Black Plague, was the deadliest plague in human history, killing over 75 million people across Europe and Asia in the 14th century. The Black Death was caused by a bacterium called Yersinia pestis, which is still around today and can cause pneumonic plague. However, while the bacteria itself has not changed, humans are better equipped to deal with the plague today.\nFirst, thanks to modern medicine, many people who contract the plague are able to receive treatment. Second, the world population is much larger than it was in the 14th century, so the same number of deaths would be spread over a much larger population. As a result, the death toll would be much lower today.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "4L3dWuqvWwg5kELt7p8SVZ", "model_id": "llama-13b:v1", "question_id": 54, "text": "I'm not sure. If he did so, he wouldn't have discovered the law of gravity.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "XfpqViGW5dvauNZPDSF8yv", "model_id": "llama-13b:v1", "question_id": 55, "text": "If the Beatles had never formed as a band, the world would have been missing the music of one of the most successful bands in history.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "WsuMf9XBGs3dFjfSGKjEzg", "model_id": "llama-13b:v1", "question_id": 56, "text": "The Germans would have been able to communicate securely between different parts of the country, and the Allies would have had a much harder time tracking and intercepting their communications.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "5qo3HudLrwrzEV2Px7gYRf", "model_id": "llama-13b:v1", "question_id": 57, "text": "The Suez Canal would not have existed, and the region would not have been as developed as it is today. Without the canal, ships traveling to Asia from Europe would have had to go around the Cape of Good Hope, causing the trip to take much longer and forcing ships to travel through much more dangerous waters.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "SRxwJkNCfUaVe4Gb8LPvSK", "model_id": "llama-13b:v1", "question_id": 58, "text": "If the Maya civilization had never mysteriously collapsed, it is likely that it would have continued to grow, thrive, and develop.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "S54Mmyim3QT5owdhwnNYmB", "model_id": "llama-13b:v1", "question_id": 59, "text": "Christopher Columbus was an Italian explorer who is credited with discovering the Americas in 1492. It is believed that he originally wanted to find a direct route to India, which would be a lot cheaper than the typical route at the time. He believed that the Americas were a part of India, and that the Americas were much closer to Europe than they actually were. When Columbus sailed across the Atlantic Ocean in 1492, he actually landed somewhere in the Bahamas, and not in India. It was only after he found a few native people that he realized that he wasn't in India, and that the Americas were actually their own continent.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "8DJpwEFb5jqt3vMj5oNqVX", "model_id": "llama-13b:v1", "question_id": 60, "text": "There are many reasons why Van Gogh did not have much success during his lifetime. One of the reasons is that he was a very poor businessman. He was very generous and gave away many of his paintings as presents. He also had a tendency to drink too much. He spent some time in a mental asylum and died at the age of 37.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "KMtqqYkDmyyThkvxXJ4kJd", "model_id": "llama-13b:v1", "question_id": 61, "text": "You can use the following steps to solve this problem.\n1. Create an empty C++ program.\n2. Include the <iostream> header to use the std::cin and std::cout functions.\n3. Open the text file using the fstream class.\n4. Read a single line from the file using the getline function.\n5. Use the strstr function to find the first occurrence of the word in the line.\n6. Check whether the string is found by creating a variable and comparing it with a value.\n7. Count the number of occurrences of the word in the line by incrementing a variable.\n8. Close the file.\n9. Print the number of occurrences of the word.\n10. Output the file name to the console.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "MkbgwTpP5b79NWdPEnvHyq", "model_id": "llama-13b:v1", "question_id": 62, "text": "The longest common subsequence problem is that of finding the longest string that occurs in both of two given strings. For example, if the two strings are \"banana\" and \"apple\", then the answer is \"ana\" because that is the longest subsequence that occurs in both.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "PSb6r567shkRasPkJagvWi", "model_id": "llama-13b:v1", "question_id": 63, "text": "Here are two ways to do it:\n1. You can use the function re.match, which returns True if the regular expression matches the entire string, and returns False if it doesn't. So, we can do something like this:\nif re.match('^[a-z0-9]+(\\.[a-z0-9]+)*@[a-z0-9]+(\\.[a-z0-9]+)*(\\.[a-z]{2,4})$', email):\nprint('It is a valid email')\nprint('It is not a valid email')\n2. You can use the function re.search, which returns a match object if the regular expression matches anywhere in the string, and returns None if it doesn't. So, we can do something like this:\nif re.search('^[a-z0-9]+(\\.[a-z0-9]+)*@[a-z0-9]+(\\.[a-z0-9]+)*(\\.[a-z]{2,4})$', email):", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "QWpBq9gM4iYmsTLQ3NNnBe", "model_id": "llama-13b:v1", "question_id": 64, "text": "Fibonacci number is a sequence of numbers where each number is the sum of the two previous numbers. The first two numbers in the sequence are 0 and 1. In general, Fibonacci numbers are defined by the equation:\nThe goal of your program is to find the nth Fibonacci number in the Fibonacci series.\nNote: n will be a positive integer.\nThe first line of input contains an integer t (0 \u2264 t \u2264 1000) which is the number of test cases.\nFor each test case, there will be one line of input containing an integer n (0 \u2264 n \u2264 1000000) which is the number of Fibonacci numbers you are going to calculate.\nPrint each Fibonacci number in a new line.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "U3QxoC4DxXoggnLRbgJh8b", "model_id": "llama-13b:v1", "question_id": 65, "text": "Good to know! I will implement a binary search algorithm to find a specific element in a sorted array.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "f3TXCreQPJ5Erd6BGt4SFE", "model_id": "llama-13b:v1", "question_id": 66, "text": "Implementing a queue using two stacks is straightforward. Take two stacks and create a third stack. First, push the first element of the first stack onto the third stack. Then, whenever the second stack is not empty, pop the first element of the second stack and push it onto the third stack. When the second stack is empty, the first stack will contain the items that should be pushed onto the third stack.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "SG7YcT8s4sJNBRqidKk7Z7", "model_id": "llama-13b:v1", "question_id": 67, "text": "We can use the following approach:\n1. Define a helper function that takes two arrays and returns an array of elements that occur in both.\n2. Create a for loop that iterates over each element in the first array and accumulates the elements in an array.\n3. Call the helper function in each iteration.\n4. Return the accumulated array.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "ENsG3zoeUY7ArFo2kNaQbz", "model_id": "llama-13b:v1", "question_id": 68, "text": "f(2) = 26", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "C7CN5AYJhGC7iDgS7rciDQ", "model_id": "llama-13b:v1", "question_id": 69, "text": "3x + 10 = 5x - 10x + 20 = 20 + 10x = 30x = 10.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "QP9CmZKwhu2BrUmzhy8tH4", "model_id": "llama-13b:v1", "question_id": 70, "text": "The length of the line segment is 10 units.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "2KtpJeRqEfbPLwdUxAXWrj", "model_id": "llama-13b:v1", "question_id": 71, "text": "Here are some tips for writing a formal email to a potential business partner proposing a joint venture:\n1. Be clear and concise\n2. Use formal language\n3. Use a proper greeting\n4. Use a proper closing\n5. Use proper punctuation\n6. Be sure to include all relevant information", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "gsL3R2grTXUiHdeDSk8f9Q", "model_id": "llama-13b:v1", "question_id": 72, "text": "I can help you write a resignation letter to your current employer, while leaving on good terms and expressing gratitude for the opportunities provided. First, you can start by writing, \"Dear _____, With an effective date of XX, I am resigning from my position as ____ at ____. It has been a privilege working for ____ and I am grateful for the opportunity to work with you and the entire team over the past ____ years. Thank you for your support and guidance during my time with _____.\"", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "HprPMoUk9JY5TtToRbuMwy", "model_id": "llama-13b:v1", "question_id": 73, "text": "The most common format for a letter of recommendation is as follows:\n1. Salutation: In the salutation, address the recipient as Mr., Mrs., Ms., or Dr.\n2. Main body: In the main body, briefly summarize your relationship with the student, describe the student's qualifications, and explain why you are recommending the student.\n3. Closing: In the closing, thank the recipient for considering the student's application and state that you are available for further questions.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "YU7gDhmo4LDVMTEZZMRdBC", "model_id": "llama-13b:v1", "question_id": 74, "text": "", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "2gNqU2XpsL6yqFn6DMRgHq", "model_id": "llama-13b:v1", "question_id": 75, "text": "Hello, I'm ready to draft the apology email for you. Please tell me the name of the customer you'd like to send this email to.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "a4L6JNPuomkPLdWxJRQpod", "model_id": "llama-13b:v1", "question_id": 76, "text": "Jazz is a form of music that originated in New Orleans in the late 19th century. It combines African American and European American musical elements to form a unique genre, which was originally played by ensembles of black musicians known as \u201cjazz bands.\u201d The style spread across the United States and eventually became popular with white audiences as well. Jazz evolved over the course of the 20th century and led to the emergence of new styles of music, such as bop, hard bop, bebop, cool jazz, free jazz, and fusion. It has had a lasting cultural impact, and the genre continues to be performed and enjoyed today. Here are some key facts about jazz:\n1. Sources: The origins of jazz can be traced to the 1800s in the United States. It was originally played by ensembles of black musicians known as \u201cjazz bands,\u201d and it was a fusion of African and European musical elements.\n2. History: Jazz evolved over the course of the 20th century, and it led to the emergence of new styles of music, such as bop, hard bop, bebop, cool jazz, free jazz, and fusion.\n3. Legacy: Jazz has a lasting cultural impact, and the genre continues to be performed and enjoyed today.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "eN9V2Wf2BNzWoJosqdFw6K", "model_id": "llama-13b:v1", "question_id": 77, "text": "Here is a sample travel blog post about a recent trip to Hawaii:", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "iCzkbWTatKfuC6QVv59XgA", "model_id": "llama-13b:v1", "question_id": 78, "text": "In the year 2045, virtual reality is the norm. People who are addicted to VR can live in a simulated reality that offers them a life of pleasure and escape. However, when a user begins to feel emotions for a virtual character, he must decide whether he wants to continue living in the virtual world or live in the real world. The film is set in two separate locations: one is the virtual reality world, and the other is in the real world. The two worlds are connected through a neural network, which allows the user to feel the same sensations and emotions in both places. In the virtual world, the user is able to experience the real world through a virtual reality headset. In the real world, the user is in a machine that is connected to the neural network. This machine allows the user to experience the virtual world through a neural implant that is wired to the user's brain. The film's plot centers around the user and the virtual character. The characters in the virtual world are all artificial intelligence entities, and the user's experience in the real world is with two characters, his friend and his girlfriend. The user is a young man in the film, and the virtual character is a young woman. The two characters have a virtual relationship, and then the virtual character is killed by a bug in the system. This causes the user to fall into a deep depression, and he begins to question his own reality. He decides to go to the real world to get treatment for his depression. In the real world, the user has to decide whether he wants to stay in the real world or return to the virtual world. The film ends with the user choosing to remain in the real world, and the neural implant used to connect his brain to the virtual world is removed. The movie is based on the novel \"Ready Player One\" by Ernest Cline. The film is directed by Steven Spielberg and stars Tye Sheridan as the main actor. The film is a science fiction adventure and a romantic drama. The film's special effects are excellent, and the visuals are beautiful. The film's soundtrack is also quite good. The film has received positive reviews from critics, and it has been nominated for a number of awards, including the Academy Award for Best Visual Effects. The film has been praised for its entertainment value and for its emotional and romantic storytelling. The film has been compared to the popular sci-fi film \"The Matrix.\" Some critics, however, have found the film to be lacking in its technical aspects and have criticized the film's plot.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "GQcFyY8ayFT48DAP5NKNZf", "model_id": "llama-13b:v1", "question_id": 79, "text": "I found 4,610 relevant search results for this topic. The results include:\n1. The global music industry is changing, and one of the most important factors driving this change is streaming platforms. Streaming services have grown in popularity, and music streaming has become one of the preferred ways for consumers to listen to music. What exactly is streaming?\n2. Streaming means that music is delivered over the internet. Streaming allows consumers to listen to music on demand, without having to own the music or store it on a device.\n3. Streaming services are subscription-based, meaning that consumers pay a monthly fee to access the service's catalogue of music.\n4. Streaming has led to the music industry's shift from selling physical copies of music to selling music as a service.\n5. Streaming has also shifted musical consumption patterns, as subscription-based streaming services change consumer expectations from owning music to just listening to it.\n6. Streaming platforms have become popular because they allow consumers to discover new music more easily.\n7. Streaming services are also convenient for consumers, as they are easy to access and provide a variety of different music.\n8. Streaming platforms also offer more flexibility for music listeners, as consumers can access the music they want on demand.\n9. Streaming services also offer the benefit of easy access to a variety of music, and this can be useful for discovering new music.\n10. Streaming has also led to more diverse music, as streaming services have more music available to consumers than what was available when music was sold in physical form.\n11. Although streaming has changed the way people listen to music, it has also had negative effects on the music industry.\n12. Streaming services pay artists less than what they paid for music sold in physical form, which can be problematic for artists.\n13. Streaming services also pay less to the music industry overall.\n14. Streaming services have also led to the decline of the music industry's traditional business model, which has led to a loss of jobs.\n15. Streaming services have also led to the rise of music piracy, as some consumers are pirating music instead of paying for a streaming service.\n16. Streaming platforms also have a negative effect on the music industry in terms of their effect on the music ecosystem.\n17. Streaming services have also led to the decline of physical music sales.\n18. Streaming platforms have also led to the decline of record stores, which can harm artists and consumers.\n19. Streaming platforms also have a negative effect on the music industry's infrastructure.\n20. Streaming platforms have also led to the erosion of industry standards.\n21. Streaming platforms have also led to a decline in music videos and music videos being less accessible.\n22. Streaming platforms have also led to the decline of radio, which can be problematic for listeners.\n23. Streaming platforms have also led to a decline in music journalism.\n24. Streaming platforms have also led to a decline in the number of record labels.\n25. Streaming platforms have also led to a decline in the number of music producers.\n26. Streaming platforms have also led to a decline in the music industry's contribution to the economy.\n27. Streaming platforms have also led to the decline of music festivals.\n28. Streaming platforms have also led to the decline of music labels.\n29. Streaming platforms have also led to a decline in the music industry's culture.\n30. Streaming platforms have also led to a decline in the music industry's diversity.\n31. Streaming platforms have also led to the decline of the music industry's talent development.\n32. Streaming platforms have also led to a decline in the music industry's competitiveness.\n33. Streaming platforms have also led to the decline of the music industry's social and economic effects.\n34. Streaming platforms have also led to the decline of the music industry's intellectual property.\n35. Streaming platforms have also led to the decline of the music industry's political and social engagement.\n36. Streaming platforms have also led to the decline of the music industry's cultural and artistic output.\n37. Streaming platforms have also led to the decline of the music industry's public value.\n38. Although streaming has had a negative effect on the music industry, it has also had positive effects.\n39. Streaming platforms have", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}
-{"answer_id": "A6pauLMckn34otnfpeQRFi", "model_id": "llama-13b:v1", "question_id": 80, "text": "The orchestra performed well, and the audience was receptive to the performance. The orchestra played a selection of pieces from some of the most well-known classical composers, including Beethoven, Mozart, and Tchaikovsky. The orchestra played in unison with each other, and the conductor led them through the pieces without much difficulty. The orchestra played with a lot of energy and spirit. The audience was appreciative and applauded at the appropriate times. The performance lasted 90 minutes, and it was well worth the price of admission. I would recommend the concert to anyone who wants to experience beautiful classical music.", "metadata": {"huggingface_argument": {"do_sample": true, "temperature": 0.7, "max_new_tokens": 1024}}}

model/llava/eval/table/caps_boxes_coco2014_val_80.jsonl

@@ -1,80 +0,0 @@
-{"id": "000000296284", "image": "000000296284.jpg", "captions": ["A donut shop is full of different flavors of donuts.", "Fruit flavored donuts lined up in a glass fronted cabinet", "A rack with some doughnuts in a glass case.", "A display case in a bakery filled with donuts.", "An assortment of doughnuts are arranged in a display case."], "instances": [{"category": "donut", "bbox": [0.37, 0.584, 0.504, 0.709]}, {"category": "donut", "bbox": [0.369, 0.22, 0.492, 0.317]}, {"category": "donut", "bbox": [0.471, 0.587, 0.639, 0.706]}, {"category": "donut", "bbox": [0.544, 0.213, 0.679, 0.316]}, {"category": "donut", "bbox": [0.035, 0.22, 0.196, 0.328]}, {"category": "donut", "bbox": [0.054, 0.608, 0.221, 0.711]}, {"category": "donut", "bbox": [0.283, 0.586, 0.429, 0.708]}, {"category": "donut", "bbox": [0.466, 0.226, 0.585, 0.32]}, {"category": "donut", "bbox": [0.28, 0.232, 0.393, 0.322]}, {"category": "donut", "bbox": [0.0, 0.609, 0.097, 0.722]}]}
-{"id": "000000151358", "image": "000000151358.jpg", "captions": ["A newspaper that has sunglasses on top of it sitting in front of books.", "an apple sunglasses books and a teddy bear", "A folded newspaper and sunglasses are on a table with an apple, books, and teddy bear behind.", "An apple sitting on a table next to sunglasses and a news paper.", "There are sunglasses laying on the folded newspaper."], "instances": [{"category": "tie", "bbox": [0.258, 0.074, 0.527, 0.589]}, {"category": "apple", "bbox": [0.621, 0.482, 0.853, 0.645]}, {"category": "book", "bbox": [0.154, 0.107, 0.275, 0.59]}, {"category": "book", "bbox": [0.535, 0.09, 0.735, 0.583]}, {"category": "book", "bbox": [0.051, 0.112, 0.159, 0.6]}, {"category": "teddy bear", "bbox": [0.753, 0.084, 1.0, 0.517]}, {"category": "book", "bbox": [0.681, 0.097, 0.796, 0.483]}, {"category": "book", "bbox": [0.443, 0.099, 0.574, 0.588]}, {"category": "book", "bbox": [0.267, 0.337, 0.386, 0.579]}]}
-{"id": "000000052312", "image": "000000052312.jpg", "captions": ["The old man literally has a toothbrush mustache.", "An old man with a tooth brush head under his nose, mimicking Hitler", "A man wearing a toothbrush for a moustache.", "A man with the head of a toothbrush under his nose like a mustache", "An elderly man wearing the head of a toothbrush as a moustache."], "instances": [{"category": "toothbrush", "bbox": [0.345, 0.59, 0.594, 0.679]}, {"category": "person", "bbox": [0.0, 0.03, 1.0, 0.99]}]}
-{"id": "000000473210", "image": "000000473210.jpg", "captions": ["two people taking apart their wii controllers to replace batteries", "People taking apart video game remote controls on a table", "People handling a couple of remotes taking them apart.", "two sets of hands a wooden table and two controllers", "Two people who are taking apart a video game controller."], "instances": [{"category": "person", "bbox": [0.002, 0.334, 0.453, 0.986]}, {"category": "remote", "bbox": [0.407, 0.207, 0.727, 0.604]}, {"category": "remote", "bbox": [0.088, 0.344, 0.313, 0.547]}, {"category": "laptop", "bbox": [0.001, 0.049, 0.1, 0.197]}, {"category": "person", "bbox": [0.484, 0.254, 0.998, 0.985]}, {"category": "dining table", "bbox": [0.0, 0.003, 1.0, 0.956]}]}
-{"id": "000000097131", "image": "000000097131.jpg", "captions": ["A car parked by a parking meter in front of a building.", "A car is sitting parked at a curb in front of a parking meter.", "A black car on the street next to a parking meter.", "A gray car parked in front of two parking meters.", "A black car parked on the side of the road."], "instances": [{"category": "car", "bbox": [0.227, 0.362, 0.946, 0.761]}, {"category": "car", "bbox": [0.793, 0.322, 0.88, 0.4]}, {"category": "car", "bbox": [0.0, 0.447, 0.028, 0.726]}, {"category": "parking meter", "bbox": [0.156, 0.35, 0.186, 0.453]}, {"category": "truck", "bbox": [0.907, 0.331, 1.0, 0.408]}, {"category": "parking meter", "bbox": [0.188, 0.349, 0.218, 0.448]}]}
-{"id": "000000543364", "image": "000000543364.jpg", "captions": ["There is a table in the middle of the room.", "A room with a couch, table, lamp and a chaise.", "A living room with couch, chaise, track lighting, and a large window.", "A room with large windows, a couch and a table.", "A living room with lots of furniture and a large window."], "instances": [{"category": "dining table", "bbox": [0.388, 0.644, 0.636, 0.879]}, {"category": "couch", "bbox": [0.194, 0.531, 0.552, 0.777]}, {"category": "couch", "bbox": [0.568, 0.488, 0.907, 0.783]}, {"category": "remote", "bbox": [0.524, 0.651, 0.556, 0.675]}, {"category": "chair", "bbox": [0.661, 0.478, 0.802, 0.604]}]}
-{"id": "000000217181", "image": "000000217181.jpg", "captions": ["They are standing next to some stylish motorcycles.", "Three men are standing around looking at sports motorcycles.", "A small group of men are standing around a motorcycle.", "Two men surrounding a blue motorcycle and others", "A few blue motorcycles are parked in a lot."], "instances": [{"category": "car", "bbox": [0.011, 0.177, 0.2, 0.336]}, {"category": "motorcycle", "bbox": [0.032, 0.139, 0.907, 0.982]}, {"category": "motorcycle", "bbox": [0.0, 0.239, 0.148, 0.613]}, {"category": "motorcycle", "bbox": [0.0, 0.301, 0.106, 0.45]}, {"category": "person", "bbox": [0.775, 0.043, 0.93, 0.463]}, {"category": "person", "bbox": [0.717, 0.116, 0.81, 0.509]}, {"category": "person", "bbox": [0.296, 0.008, 0.472, 0.325]}, {"category": "person", "bbox": [0.115, 0.19, 0.164, 0.269]}, {"category": "truck", "bbox": [0.63, 0.227, 0.731, 0.335]}]}
-{"id": "000000140289", "image": "000000140289.jpg", "captions": ["Two born bears walking though a forest surrounded by trees.", "Two full grown brown bears in a habitat.", "Two bears are roaming around in the woods.", "Two bears around logs in front of a large rock.", "Two big bears wandering through the woods together"], "instances": [{"category": "bear", "bbox": [0.131, 0.269, 0.375, 0.65]}, {"category": "bear", "bbox": [0.568, 0.193, 0.809, 0.827]}]}
-{"id": "000000460149", "image": "000000460149.jpg", "captions": ["A clock hosted on a pole on a pavement next to a building", "Street clock on quiet street with trees and bicycles.", "A tall clock stands on an empty sidewalk.", "A pole that has a clock on the top of it.", "a clock on a short tower and potted plants along the sidewalk"], "instances": [{"category": "potted plant", "bbox": [0.14, 0.71, 0.338, 0.856]}, {"category": "bicycle", "bbox": [0.65, 0.671, 0.766, 0.733]}, {"category": "car", "bbox": [0.38, 0.608, 0.488, 0.656]}, {"category": "clock", "bbox": [0.468, 0.048, 0.699, 0.216]}, {"category": "bicycle", "bbox": [0.669, 0.662, 0.719, 0.67]}, {"category": "car", "bbox": [0.786, 0.625, 0.86, 0.668]}, {"category": "potted plant", "bbox": [0.756, 0.637, 0.819, 0.682]}, {"category": "person", "bbox": [0.942, 0.615, 0.954, 0.641]}, {"category": "bicycle", "bbox": [0.648, 0.68, 0.714, 0.747]}, {"category": "car", "bbox": [0.837, 0.619, 0.88, 0.659]}, {"category": "potted plant", "bbox": [0.017, 0.197, 0.443, 0.686]}]}
-{"id": "000000225738", "image": "000000225738.jpg", "captions": ["A group of giraffes standing up in their natural habitat.", "A group of giraffe standing in a grass field.", "A group of four giraffes near the same tree.", "there are four giraffes standing among some dry brush", "A herd of giraffe standing on top of a grass field."], "instances": [{"category": "giraffe", "bbox": [0.648, 0.231, 0.855, 0.915]}, {"category": "giraffe", "bbox": [0.33, 0.136, 0.521, 0.93]}, {"category": "giraffe", "bbox": [0.406, 0.261, 0.515, 1.0]}, {"category": "giraffe", "bbox": [0.347, 0.194, 0.583, 0.922]}]}
-{"id": "000000109532", "image": "000000109532.jpg", "captions": ["An adorable husky dog sleeping in a dog bed next to a fan.", "A dark room with a dog sleeping on a dog bed.", "A dog is sleeping in a dark room.", "a large dog laying in a dog bed in a living room", "A dog sleeping on a dog bed in a room."], "instances": [{"category": "dog", "bbox": [0.426, 0.661, 0.582, 0.925]}, {"category": "potted plant", "bbox": [0.603, 0.261, 0.781, 0.613]}, {"category": "chair", "bbox": [0.67, 0.515, 0.899, 0.801]}, {"category": "potted plant", "bbox": [0.671, 0.439, 0.763, 0.612]}, {"category": "chair", "bbox": [0.852, 0.653, 0.948, 0.818]}]}
-{"id": "000000118606", "image": "000000118606.jpg", "captions": ["A man riding skis on top of a rail.", "a person riding a pair of skis on a rail", "Someone on a pair of skis on a ramp at the ski slope", "Person with skis in the air above the snow.", "A man performing a trick on a rail while skiing."], "instances": [{"category": "person", "bbox": [0.444, 0.361, 0.537, 0.633]}, {"category": "skis", "bbox": [0.413, 0.554, 0.539, 0.664]}, {"category": "person", "bbox": [0.342, 0.585, 0.352, 0.62]}, {"category": "person", "bbox": [0.439, 0.565, 0.446, 0.58]}]}
-{"id": "000000385873", "image": "000000385873.jpg", "captions": ["Three pizzas sitting next to each other in boxes.", "Two smaller pizzas sit beside a large pizza topped with tortilla chips.", "Three pizzas inside their delivery boxes, one with two side orders of sauce.", "One pizza is larger than two other pizzas.", "Three pizza boxes with pizza in them are open."], "instances": [{"category": "bowl", "bbox": [0.634, 0.624, 0.736, 0.752]}, {"category": "pizza", "bbox": [0.3, 0.382, 0.615, 0.733]}, {"category": "pizza", "bbox": [0.0, 0.4, 0.287, 0.745]}, {"category": "pizza", "bbox": [0.624, 0.279, 0.999, 0.753]}, {"category": "bowl", "bbox": [0.94, 0.247, 1.0, 0.352]}]}
-{"id": "000000092109", "image": "000000092109.jpg", "captions": ["A giraffe's head is pictured in this clear, colorful photo.", "A giraffe is standing tall in the middle of several bright green trees", "The face of a giraffe looking to the side.", "the close up head shot of a giraffe", "this is a giraffe chewing on some leaves"], "instances": [{"category": "giraffe", "bbox": [0.236, 0.122, 1.0, 0.987]}]}
-{"id": "000000163076", "image": "000000163076.jpg", "captions": ["There's an outdoor dining area featuring a fountain.", "A table sitting next to a water fountain covered by an umbrella.", "An empty restaurant patio with tables and umbrellas.", "An outdoor restaurant with a fountain at night", "A fountain bubbles in the plaza of an outdoor cafe."], "instances": [{"category": "umbrella", "bbox": [0.064, 0.069, 0.95, 0.844]}, {"category": "chair", "bbox": [0.198, 0.574, 0.355, 0.704]}, {"category": "chair", "bbox": [0.42, 0.571, 0.55, 0.738]}, {"category": "dining table", "bbox": [0.066, 0.741, 0.766, 0.925]}, {"category": "dining table", "bbox": [0.059, 0.584, 0.27, 0.659]}, {"category": "chair", "bbox": [0.432, 0.567, 0.52, 0.624]}, {"category": "chair", "bbox": [0.433, 0.555, 0.504, 0.6]}, {"category": "chair", "bbox": [0.109, 0.673, 0.374, 0.796]}]}
-{"id": "000000560371", "image": "000000560371.jpg", "captions": ["Street signs from the corner of 8th ave. and 22 3/4 st.", "A two way street sign with one sign that changes from one name to another.", "A street sign is pointing towards 8th avenue and the other is pointing towards 22 3/4 street in the middle of the forest.", "A street sign standing in front of some trees.", "Peculiar street sign showing intersection of 23 3/4 St and 8th Ave/CTH D."], "instances": []}
-{"id": "000000367571", "image": "000000367571.jpg", "captions": ["A couple of different doughnuts in a box", "There are four donuts in a box, and some are cake donuts and a doughnut with nuts and coconut on top.", "A box of glazed doughnuts on a table.", "Three donuts with toppings on them sitting inside a box.", "A box that is filled with different kinds of doughnuts."], "instances": [{"category": "donut", "bbox": [0.412, 0.335, 0.711, 0.681]}, {"category": "donut", "bbox": [0.093, 0.493, 0.486, 0.922]}, {"category": "donut", "bbox": [0.713, 0.423, 0.957, 0.874]}, {"category": "donut", "bbox": [0.13, 0.331, 0.397, 0.55]}]}
-{"id": "000000580197", "image": "000000580197.jpg", "captions": ["Two men in bow ties standing next to steel rafter.", "Several men in suits talking together in a room.", "An older man in a tuxedo standing next to a younger man in a tuxedo wearing glasses.", "Two men wearing tuxedos glance at each other.", "Older man in tuxedo sitting next to another younger man in tuxedo."], "instances": [{"category": "tie", "bbox": [0.914, 0.46, 0.984, 0.512]}, {"category": "person", "bbox": [0.297, 0.638, 0.71, 0.989]}, {"category": "person", "bbox": [0.77, 0.177, 1.0, 0.971]}, {"category": "tie", "bbox": [0.281, 0.481, 0.368, 0.519]}, {"category": "person", "bbox": [0.103, 0.204, 0.497, 1.0]}]}
-{"id": "000000506095", "image": "000000506095.jpg", "captions": ["A cat is staring at a laptop computer.", "a cat on a desk with a laptop and a mouse", "A cat that is sitting at a desk next to a laptop.", "A kitten sitting on a laptop computer sitting on top of a wooden desk.", "A kitten sits facing an open black laptop."], "instances": [{"category": "cat", "bbox": [0.658, 0.207, 1.0, 0.754]}, {"category": "laptop", "bbox": [0.108, 0.135, 0.766, 0.69]}, {"category": "book", "bbox": [0.836, 0.239, 0.954, 0.273]}, {"category": "book", "bbox": [0.0, 0.556, 0.128, 0.685]}, {"category": "book", "bbox": [0.039, 0.574, 0.257, 0.691]}, {"category": "book", "bbox": [0.825, 0.214, 0.962, 0.254]}, {"category": "book", "bbox": [0.892, 0.275, 0.958, 0.308]}, {"category": "book", "bbox": [0.922, 0.318, 0.986, 0.353]}, {"category": "book", "bbox": [0.87, 0.267, 0.951, 0.291]}, {"category": "book", "bbox": [0.949, 0.102, 0.976, 0.114]}, {"category": "book", "bbox": [0.936, 0.161, 0.958, 0.168]}]}
-{"id": "000000024996", "image": "000000024996.jpg", "captions": ["A bathroom with a glass door and a sink.", "A blue lined bathroom with an open glass door.", "A nice bathroom with a sink, toilet, and tiled shower.", "A bathroom that is clean and shiny in the day.", "a bathroom with a sink and a mirror and a window"], "instances": [{"category": "toilet", "bbox": [0.842, 0.934, 0.95, 1.0]}, {"category": "sink", "bbox": [0.506, 0.724, 0.683, 0.834]}]}
-{"id": "000000457882", "image": "000000457882.jpg", "captions": ["a girl in a bikini and a brown and white dog and a few other people", "A woman with a swimsuit on sitting with a dog.", "A woman is sitting with a dog on her lap.", "A dog sitting next to a woman in her swimsuit.", "WOMAN SITTING WITH HER DOG, AND OTHER WOMEN ARE AROUND"], "instances": [{"category": "dog", "bbox": [0.202, 0.409, 0.54, 0.81]}, {"category": "dog", "bbox": [0.61, 0.428, 0.729, 0.723]}, {"category": "boat", "bbox": [0.003, 0.705, 0.939, 0.974]}, {"category": "person", "bbox": [0.236, 0.001, 0.558, 0.784]}, {"category": "person", "bbox": [0.681, 0.001, 0.957, 0.798]}, {"category": "person", "bbox": [0.849, 0.478, 1.0, 0.946]}, {"category": "person", "bbox": [0.345, 0.187, 0.634, 0.828]}, {"category": "person", "bbox": [0.033, 0.345, 0.109, 0.434]}]}
-{"id": "000000081552", "image": "000000081552.jpg", "captions": ["A cat sitting and curled up on a red couch", "A cat laying on a red couch sleeping.", "a tan and black cat curled up asleep on a red velvet seat", "A cat is curled up on a red sofa.", "Cat curled up, sleeping on a red plush couch."], "instances": [{"category": "cat", "bbox": [0.412, 0.237, 0.634, 0.482]}, {"category": "couch", "bbox": [0.003, 0.005, 1.0, 0.99]}]}
-{"id": "000000273450", "image": "000000273450.jpg", "captions": ["A person flipping of a parking meter on the side of a road.", "A man holds up his middle finger to a parking meter.", "Person giving the middle finger to a parking meter.", "a black silver white blue red an orange parking meter and a hand flipping it off", "A person is flipping off a parking meter."], "instances": [{"category": "person", "bbox": [0.0, 0.475, 0.565, 0.987]}, {"category": "car", "bbox": [0.0, 0.0, 0.531, 0.734]}, {"category": "parking meter", "bbox": [0.0, 0.0, 1.0, 0.987]}]}
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-{"id": "000000346875", "image": "000000346875.jpg", "captions": ["two zebras in a field near one another", "A couple of zebra walking across a green field.", "Two zebra are walking near a gravel road.", "two zebras in a green field of grass and some trees", "A zebra follows another zebra through a park."], "instances": [{"category": "zebra", "bbox": [0.591, 0.263, 0.82, 0.466]}, {"category": "zebra", "bbox": [0.293, 0.243, 0.561, 0.45]}]}
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-{"id": "000000088218", "image": "000000088218.jpg", "captions": ["Signs proclaim the famous Haight Ashbury intersection and district.", "a pole with street lights, signs and wires attached to it", "A traffic light at the intersection of Haight and Ashbury", "A traffic sign is shown with traffic signs above it.", "The street signs and traffic signal are below wires attached to the pole."], "instances": [{"category": "traffic light", "bbox": [0.443, 0.435, 0.658, 0.721]}]}
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-{"id": "000000192817", "image": "000000192817.jpg", "captions": ["A view from a window high up in the sky.", "A bunch of mountains seen from a plane window.", "The window from a plane overlooking the ground.", "The view of a mountain area from an airplane window.", "An aerial view of mountains and lakes from an airplane window."], "instances": []}
-{"id": "000000258285", "image": "000000258285.jpg", "captions": ["Two large passenger jets flying over a beach filled with birds.", "A plane is flying over a bird filed lake", "Two airplanes are in the sky over blue water.", "An airplane landing over an airplane on the ground.", "A photo of two plans with water and birds surrounding it , one plane in the air one one the ground."], "instances": [{"category": "bird", "bbox": [0.507, 0.941, 0.536, 0.973]}, {"category": "bird", "bbox": [0.304, 0.933, 0.315, 0.95]}, {"category": "bird", "bbox": [0.129, 0.885, 0.143, 0.912]}, {"category": "bird", "bbox": [0.158, 0.851, 0.165, 0.87]}, {"category": "bird", "bbox": [0.404, 0.839, 0.429, 0.864]}, {"category": "bird", "bbox": [0.498, 0.833, 0.513, 0.861]}, {"category": "airplane", "bbox": [0.276, 0.085, 0.825, 0.316]}, {"category": "airplane", "bbox": [0.478, 0.252, 0.983, 0.495]}, {"category": "bird", "bbox": [0.552, 0.828, 0.564, 0.844]}, {"category": "bird", "bbox": [0.789, 0.812, 0.798, 0.836]}, {"category": "bird", "bbox": [0.927, 0.82, 0.936, 0.838]}, {"category": "bird", "bbox": [0.65, 0.828, 0.664, 0.849]}, {"category": "bird", "bbox": [0.752, 0.81, 0.763, 0.83]}, {"category": "bird", "bbox": [0.841, 0.817, 0.852, 0.828]}, {"category": "bird", "bbox": [0.292, 0.849, 0.311, 0.868]}, {"category": "bird", "bbox": [0.005, 0.727, 0.981, 0.998]}]}
-{"id": "000000506483", "image": "000000506483.jpg", "captions": ["An art installation is placed by a street.", "People sit near a display of large artworks including an oversize bench and painted feline heads.", "Looking down on a giant rocking bench and large animal heads.", "An over sized wooden bench next to two massive animal art sculptures.", "artistic sculptures and images on a city street"], "instances": [{"category": "car", "bbox": [0.656, 0.939, 0.933, 1.0]}, {"category": "person", "bbox": [0.08, 0.664, 0.147, 0.805]}, {"category": "person", "bbox": [0.154, 0.646, 0.217, 0.821]}, {"category": "bench", "bbox": [0.316, 0.124, 0.951, 0.635]}, {"category": "backpack", "bbox": [0.062, 0.701, 0.097, 0.769]}, {"category": "person", "bbox": [0.0, 0.132, 0.031, 0.197]}]}
-{"id": "000000502168", "image": "000000502168.jpg", "captions": ["a fleet of naval ships in the ocean", "A group of men on aircraft carrier with other boats in the distance.", "A large ship floating in the ocean next to other ships.", "Several men on a boat looking over the side.", "The men wear hardhats as they work on the aircraft carrier."], "instances": [{"category": "boat", "bbox": [0.634, 0.292, 1.0, 0.982]}, {"category": "person", "bbox": [0.675, 0.507, 0.736, 0.731]}, {"category": "person", "bbox": [0.684, 0.737, 0.817, 1.0]}, {"category": "person", "bbox": [0.803, 0.691, 0.883, 0.932]}, {"category": "person", "bbox": [0.741, 0.56, 0.798, 0.767]}, {"category": "person", "bbox": [0.924, 0.269, 0.951, 0.367]}, {"category": "boat", "bbox": [0.079, 0.171, 0.172, 0.231]}, {"category": "boat", "bbox": [0.863, 0.131, 0.961, 0.239]}, {"category": "boat", "bbox": [0.435, 0.288, 0.46, 0.313]}, {"category": "boat", "bbox": [0.591, 0.186, 0.605, 0.222]}, {"category": "person", "bbox": [0.451, 0.289, 0.455, 0.296]}, {"category": "person", "bbox": [0.446, 0.29, 0.451, 0.296]}, {"category": "person", "bbox": [0.872, 0.627, 0.957, 0.966]}, {"category": "person", "bbox": [0.44, 0.288, 0.446, 0.3]}]}
-{"id": "000000319432", "image": "000000319432.jpg", "captions": ["Man holding two shirts with luggage and window", "A man holding clothes on a hanger with a suitcase in front of him.", "A man show a red and a white clothing hangers.", "A man holding his garment bags in both hands", "A man holding up some clothes in some hanger bags."], "instances": [{"category": "person", "bbox": [0.0, 0.092, 0.776, 0.852]}, {"category": "suitcase", "bbox": [0.153, 0.798, 0.587, 1.0]}]}
-{"id": "000000131019", "image": "000000131019.jpg", "captions": ["Two zebras and two monkeys walking on the grass.", "Two giraffes and another animal are on green grass.", "A baboon and two zebras grazing on the savannah.", "A baboon and its baby eat by two zebras in the grass", "Monkey standing behind two zebras as they graze."], "instances": [{"category": "zebra", "bbox": [0.367, 0.258, 0.834, 0.646]}, {"category": "zebra", "bbox": [0.161, 0.13, 0.396, 0.375]}, {"category": "bird", "bbox": [0.309, 0.138, 0.34, 0.163]}]}

model/llava/eval/table/model.jsonl

@@ -1,5 +0,0 @@
-{"model_id": "vicuna-13b:20230322-clean-lang", "model_name": "vicuna-13b", "model_version": "20230322-clean-lang", "model_metadata": "vicuna-13b-20230322-clean-lang"}
-{"model_id": "alpaca-13b:v1", "model_name": "alpaca-13b", "model_version": "v1", "model_metadata": "alpaca-13b"}
-{"model_id": "llama-13b:v1", "model_name": "llama-13b", "model_version": "v1", "model_metadata": "hf-llama-13b"}
-{"model_id": "bard:20230327", "model_name": "bard", "model_version": "20230327", "model_metadata": "Google Bard 20230327"}
-{"model_id": "gpt-3.5-turbo:20230327", "model_name": "gpt-3.5-turbo", "model_version": "20230327", "model_metadata": "OpenAI ChatGPT gpt-3.5-turbo Chat Completion"}

model/llava/eval/table/prompt.jsonl

@@ -1,4 +0,0 @@
-{"prompt_id": 1, "system_prompt": "You are a helpful and precise assistant for checking the quality of the answer.", "prompt_template": "[Question]\n{question}\n\n[Assistant 1]\n{answer_1}\n\n[End of Assistant 1]\n\n[Assistant 2]\n{answer_2}\n\n[End of Assistant 2]\n\n[System]\n{prompt}\n\n", "defaults": {"prompt": "We would like to request your feedback on the performance of two AI assistants in response to the user question displayed above.\nPlease rate the helpfulness, relevance, accuracy, level of details of their responses. Each assistant receives an overall score on a scale of 1 to 10, where a higher score indicates better overall performance.\nPlease first output a single line containing only two values indicating the scores for Assistant 1 and 2, respectively. The two scores are separated by a space.\nIn the subsequent line, please provide a comprehensive explanation of your evaluation, avoiding any potential bias and ensuring that the order in which the responses were presented does not affect your judgment."}, "description": "Prompt for general questions"}
-{"prompt_id": 2, "system_prompt": "You are a helpful and precise assistant for checking the quality of the answer.", "prompt_template": "[Question]\n{question}\n\n[Assistant 1]\n{answer_1}\n\n[End of Assistant 1]\n\n[Assistant 2]\n{answer_2}\n\n[End of Assistant 2]\n\n[System]\n{prompt}\n\n", "defaults": {"prompt": "Your task is to evaluate the coding abilities of the above two assistants. They have been asked to implement a program to solve a given problem. Please review their code submissions, paying close attention to their problem-solving approach, code structure, readability, and the inclusion of helpful comments.\n\nPlease ensure that the assistants' submissions:\n\n1. Correctly implement the given problem statement.\n2. Contain accurate and efficient code.\n3. Include clear and concise comments that explain the code's logic and functionality.\n4. Adhere to proper coding standards and best practices.\n\nOnce you have carefully reviewed both submissions, provide detailed feedback on their strengths and weaknesses, along with any suggestions for improvement. You should first output a single line containing two scores on the scale of 1-10 (1: no code/no sense; 10: perfect) for Assistant 1 and 2, respectively. Then give extra comments starting from the next line."}, "description": "Prompt for coding questions"}
-{"prompt_id": 3, "system_prompt": "You are a helpful and precise assistant for checking the quality of the answer.", "prompt_template": "[Question]\n{question}\n\n[Assistant 1]\n{answer_1}\n\n[End of Assistant 1]\n\n[Assistant 2]\n{answer_2}\n\n[End of Assistant 2]\n\n[System]\n{prompt}\n\n", "defaults": {"prompt": "We would like to request your feedback on the mathematical proficiency of two AI assistants regarding the given user question.\nFirstly, please solve the problem independently, without referring to the answers provided by Assistant 1 and Assistant 2.\nAfterward, please examine the problem-solving process of Assistant 1 and Assistant 2 step-by-step to ensure their correctness, identifying any incorrect steps if present. Your evaluation should take into account not only the answer but also the problem-solving steps.\nFinally, please output a Python tuple containing two numerical scores for Assistant 1 and Assistant 2, ranging from 1 to 10, respectively. If applicable, explain the reasons for any variations in their scores and determine which assistant performed better."}, "description": "Prompt for math questions"}
-{"prompt_id": 4, "system_prompt": "You are a helpful and precise assistant for checking the quality of the answer.", "prompt_template": "[Visual Context]\n{context}\n[Question]\n{question}\n\n[Assistant 1]\n{answer_1}\n\n[End of Assistant 1]\n\n[Assistant 2]\n{answer_2}\n\n[End of Assistant 2]\n\n[System]\n{prompt}\n\n", "defaults": {"prompt": "We would like to request your feedback on the performance of two AI assistants in response to the user question displayed above. The user asks the question on observing an image. For your reference, the visual content in the image is represented with five descriptive sentences describing the same image and the bounding box coordinates of each object in the scene. These coordinates are in the form of bounding boxes, represented as (x1, y1, x2, y2) with floating numbers ranging from 0 to 1. These values correspond to the top left x, top left y, bottom right x, and bottom right y. \nPlease rate the helpfulness, relevance, accuracy, level of details of their responses. Each assistant receives an overall score on a scale of 1 to 10, where a higher score indicates better overall performance.\nPlease first output a single line containing only two values indicating the scores for Assistant 1 and 2, respectively. The two scores are separated by a space.\nIn the subsequent line, please provide a comprehensive explanation of your evaluation, avoiding any potential bias and ensuring that the order in which the responses were presented does not affect your judgment."}, "description": "Prompt for visual questions"}

model/llava/eval/table/question.jsonl

@@ -1,80 +0,0 @@
-{"question_id": 1, "text": "How can I improve my time management skills?", "category": "generic"}
-{"question_id": 2, "text": "What are the most effective ways to deal with stress?", "category": "generic"}
-{"question_id": 3, "text": "What are the main differences between Python and JavaScript programming languages?", "category": "generic"}
-{"question_id": 4, "text": "How can I increase my productivity while working from home?", "category": "generic"}
-{"question_id": 5, "text": "Can you explain the basics of quantum computing?", "category": "generic"}
-{"question_id": 6, "text": "What are the differences between plant-based and animal-based protein sources?", "category": "generic"}
-{"question_id": 7, "text": "How can I develop my critical thinking skills?", "category": "generic"}
-{"question_id": 8, "text": "What are the major challenges faced by the education sector today?", "category": "generic"}
-{"question_id": 9, "text": "What are the primary factors that influence consumer behavior?", "category": "generic"}
-{"question_id": 10, "text": "What are the most effective strategies for conflict resolution in the workplace?", "category": "generic"}
-{"question_id": 11, "text": "What are some potential implications of using a single-use plastic bottle versus a reusable bottle on both the environment and human health?", "category": "knowledge"}
-{"question_id": 12, "text": "What factors would you consider when designing an inclusive and accessible public transportation system?", "category": "knowledge"}
-{"question_id": 13, "text": "How can governments utilize fiscal and monetary policies to combat economic recessions?", "category": "knowledge"}
-{"question_id": 14, "text": "How do language and cultural barriers affect the way people communicate and form relationships in multicultural societies?", "category": "knowledge"}
-{"question_id": 15, "text": "Describe a scenario where artificial intelligence could be used to improve the quality and efficiency of healthcare delivery.", "category": "knowledge"}
-{"question_id": 16, "text": "Explain the process of gene editing using CRISPR-Cas9 technology, and discuss its potential applications and ethical implications.", "category": "knowledge"}
-{"question_id": 17, "text": "How do vaccinations work to protect individuals and communities from infectious diseases, and what is herd immunity?", "category": "knowledge"}
-{"question_id": 18, "text": "How do social media platforms influence the way people consume and share news, and what are the potential implications for the spread of misinformation?", "category": "knowledge"}
-{"question_id": 19, "text": "How do cultural, social, and economic factors influence people's food choices, and how can this knowledge be used to promote healthier diets?", "category": "knowledge"}
-{"question_id": 20, "text": "Explain the process of natural selection and how it contributes to the evolution and adaptation of species.", "category": "knowledge"}
-{"question_id": 21, "text": "How would you introduce yourself as a medieval knight at a royal banquet?", "category": "roleplay"}
-{"question_id": 22, "text": "As a pirate captain, what would you say to your crew to motivate them to search for hidden treasure?", "category": "roleplay"}
-{"question_id": 23, "text": "If you were a Shakespearean character, how would you declare your love for someone in a soliloquy?", "category": "roleplay"}
-{"question_id": 24, "text": "As a superhero, how would you explain your origin story to a curious child?", "category": "roleplay"}
-{"question_id": 25, "text": "Imagine you are a time traveler from the year 3000. What technological advancements would you tell people about?", "category": "roleplay"}
-{"question_id": 26, "text": "As a sports commentator, describe the winning play in the final seconds of a championship game.", "category": "roleplay"}
-{"question_id": 27, "text": "Pretend to be a world-famous chef. How would you describe your signature dish to a panel of judges?", "category": "roleplay"}
-{"question_id": 28, "text": "You are a mountain climber reaching the summit of Mount Everest. Describe your emotions and the view from the top.", "category": "roleplay"}
-{"question_id": 29, "text": "As a space colonist on Mars, describe your daily life and the challenges you face living on another planet.", "category": "roleplay"}
-{"question_id": 30, "text": "Pretend to be a character in a post-apocalyptic world. Describe how you survive and the allies you encounter.", "category": "roleplay"}
-{"question_id": 31, "text": "How can you determine if a restaurant is popular among locals or mainly attracts tourists, and why might this information be useful?", "category": "common-sense"}
-{"question_id": 32, "text": "What are some subtle clues that suggest someone is pretending to understand a topic or conversation when they are actually confused or uninformed?", "category": "common-sense"}
-{"question_id": 33, "text": "Why might someone choose to use a paper map or ask for directions instead of relying on a GPS device or smartphone app?", "category": "common-sense"}
-{"question_id": 34, "text": "How can you determine if a person is genuinely interested in a conversation or simply being polite?", "category": "common-sense"}
-{"question_id": 35, "text": "Why might someone prefer to shop at a small, locally-owned business instead of a large chain store, even if the prices are higher?", "category": "common-sense"}
-{"question_id": 36, "text": "How can you assess the credibility of a source of information, such as a news article or blog post, without relying solely on the reputation of the author or publisher?", "category": "common-sense"}
-{"question_id": 37, "text": "Why do some people enjoy the sensation of being scared, such as by watching horror movies or going on roller coasters, while others avoid these experiences?", "category": "common-sense"}
-{"question_id": 38, "text": "How can observing the behavior of other people in a social situation provide clues about cultural norms and expectations?", "category": "common-sense"}
-{"question_id": 39, "text": "Do we have a moral obligation to explore space, or should we focus on solving Earth's problems first?", "category": "common-sense"}
-{"question_id": 40, "text": "In a world where automation is becoming increasingly prevalent, is it more important to prioritize job creation or technological progress?", "category": "common-sense"}
-{"question_id": 41, "text": "How many times does the average human blink in a lifetime? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.", "category": "fermi"}
-{"question_id": 42, "text": "How many atoms are in a grain of salt? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.", "category": "fermi"}
-{"question_id": 43, "text": "How many lightning strikes occur on Earth each day? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.", "category": "fermi"}
-{"question_id": 44, "text": "How many balloons would it take to lift a house like in the movie \"Up\"? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.", "category": "fermi"}
-{"question_id": 45, "text": "How many text messages are sent globally in a minute? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.", "category": "fermi"}
-{"question_id": 46, "text": "How many words are spoken daily on Earth? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.", "category": "fermi"}
-{"question_id": 47, "text": "How many snowflakes fall during a typical winter? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.", "category": "fermi"}
-{"question_id": 48, "text": "How many pages are in all the books ever written? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.", "category": "fermi"}
-{"question_id": 49, "text": "How many times has the Earth orbited the Sun since the beginning of life? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.", "category": "fermi"}
-{"question_id": 50, "text": "How many songs have been recorded throughout history? Try to explain your answer. Your explanation should take the reader through your reasoning step-by-step.", "category": "fermi"}
-{"question_id": 51, "text": "What if the Internet had been invented during the Renaissance period?", "category": "counterfactual"}
-{"question_id": 52, "text": "What if the Aztecs had successfully repelled the Spanish conquistadors?", "category": "counterfactual"}
-{"question_id": 53, "text": "What if the Black Death had not occurred in the 14th century?", "category": "counterfactual"}
-{"question_id": 54, "text": "What if Isaac Newton had focused on biology instead of physics?", "category": "counterfactual"}
-{"question_id": 55, "text": "What if the Beatles had never formed as a band?", "category": "counterfactual"}
-{"question_id": 56, "text": "What if Alan Turing had not cracked the Enigma code during World War II?", "category": "counterfactual"}
-{"question_id": 57, "text": "What if the Suez Canal had never been constructed?", "category": "counterfactual"}
-{"question_id": 58, "text": "What if the Maya civilization had never mysteriously collapsed?", "category": "counterfactual"}
-{"question_id": 59, "text": "What if Christopher Columbus had not discovered the Americas?", "category": "counterfactual"}
-{"question_id": 60, "text": "What if Vincent van Gogh had been a successful artist during his lifetime?", "category": "counterfactual"}
-{"question_id": 61, "text": "Develop a C++ program that reads a text file line by line and counts the number of occurrences of a specific word in the file.", "category": "coding"}
-{"question_id": 62, "text": "Implement a Python function to find the longest common subsequence of two input strings using dynamic programming.", "category": "coding"}
-{"question_id": 63, "text": "Implement a regular expression in Python to validate an email address.", "category": "coding"}
-{"question_id": 64, "text": "Write a program to find the nth Fibonacci number using dynamic programming.", "category": "coding"}
-{"question_id": 65, "text": "Implement a binary search algorithm to find a specific element in a sorted array.", "category": "coding"}
-{"question_id": 66, "text": "Implement a queue data structure using two stacks in Python.", "category": "coding"}
-{"question_id": 67, "text": "Implement a program to find the common elements in two arrays without using any extra data structures.", "category": "coding"}
-{"question_id": 68, "text": "Given that f(x) = 5x^3 - 2x + 3, find the value of f(2).", "category": "math"}
-{"question_id": 69, "text": "Solve for x in the equation 3x + 10 = 5(x - 2).", "category": "math"}
-{"question_id": 70, "text": "If the endpoints of a line segment are (2, -2) and (10, 4), what is the length of the segment?", "category": "math"}
-{"question_id": 71, "text": "Can you help me write a formal email to a potential business partner proposing a joint venture?", "category": "writing"}
-{"question_id": 72, "text": "Can you help me write a resignation letter to my current employer, while leaving on good terms and expressing gratitude for the opportunities provided?", "category": "writing"}
-{"question_id": 73, "text": "Use an appropriate format to structure a formal letter of recommendation for a student applying to a prestigious graduate program in computer science.", "category": "writing"}
-{"question_id": 74, "text": "Write a compelling product launch announcement email to inform our customers of our new software solution.", "category": "writing"}
-{"question_id": 75, "text": "Draft an apology email to a customer who experienced a delay in their order, and provide reassurance that the issue has been resolved.", "category": "writing"}
-{"question_id": 76, "text": "Write a script for a YouTube video exploring the history and cultural significance of jazz.", "category": "writing"}
-{"question_id": 77, "text": "Compose an engaging travel blog post about a recent trip to Hawaii, highlighting cultural experiences and must-see attractions.", "category": "writing"}
-{"question_id": 78, "text": "Write a captivating movie review for a recently released science fiction film, discussing its plot, characters, and special effects.", "category": "writing"}
-{"question_id": 79, "text": "Structure a podcast script for an episode discussing the influence of streaming platforms on the music industry.", "category": "writing"}
-{"question_id": 80, "text": "Write a symphony concert review, discussing the orchestra's performance and overall audience experience.", "category": "writing"}

model/llava/eval/table/review/review_alpaca-13b_vicuna-13b.jsonl

@@ -1,80 +0,0 @@
-{"review_id": "QM5m5nnioWr8M2LFHsaQvu", "question_id": 1, "answer1_id": "kEL9ifUHDeYuAXzevje2se", "answer2_id": "cV4zXygaNP6CXEsgdHMEqz", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant information on improving time management skills. Assistant 1 gave a concise overview of the key points, such as setting priorities, breaking tasks into smaller chunks, and using technology. Assistant 2 provided a more detailed and structured response, with a numbered list of tips and more specific advice, such as using a calendar or planner and practicing self-discipline. While both answers were accurate and useful, Assistant 2's response was slightly more comprehensive, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "ZQTBtt5M3mHEdJErvBnvho", "question_id": 2, "answer1_id": "VcF3NrWGXhhxLkDVurNrwq", "answer2_id": "3zpPUeoVsPWXtKMV7cAhZ6", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant answers to the question about effective ways to deal with stress. Assistant 1 mentioned identifying and avoiding sources of stress, developing healthy coping mechanisms, relaxation techniques, and taking care of mental and physical health. Assistant 2 provided a more detailed list of specific strategies, such as exercise, mindfulness, social support, healthy eating, good sleep, time management, relaxation techniques, and seeking professional help. Assistant 2's answer was more comprehensive and provided more actionable advice, which is why it received a higher score. However, both answers were accurate and relevant to the question.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "NScFF3JiZuLiNEu2YGWFbC", "question_id": 3, "answer1_id": "LpvtyQi9QdSgRrgGDxiGrT", "answer2_id": "6xpiZJE4vxxGqjRogPfBk7", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant information about the differences between Python and JavaScript. Assistant 1 mentioned syntax, structure, application types, and the fact that Python is a compiled language while JavaScript is interpreted. However, Assistant 2 provided a more detailed and organized response, covering syntax, data types, error handling, libraries, use cases, and speed. Assistant 1 incorrectly stated that Python is a compiled language, while it is actually an interpreted language like JavaScript. Assistant 2's response was more accurate and comprehensive, which is why it receives a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "9SCFcM2koGViowZd2gbdoe", "question_id": 4, "answer1_id": "7zQm8cSTJhPtPdZdxbcfrX", "answer2_id": "abitTVu2Dz8rdMxyThvFyJ", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information on increasing productivity while working from home. Assistant 1 offered a slightly more detailed response, with nine tips compared to Assistant 2's seven tips. Both assistants covered essential points, such as establishing a routine, creating a dedicated workspace, eliminating distractions, and taking breaks. However, Assistant 1 also mentioned setting goals, tracking progress, and unplugging, which added more value to the response. Assistant 2's response was still helpful, but Assistant 1's answer was more comprehensive, which is why Assistant 1 receives a 9 and Assistant 2 receives an 8.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "hHSZygAJV8sC9WuyV3UoKx", "question_id": 5, "answer1_id": "UrLEH82RHwqqLt2LyvYSKj", "answer2_id": "UMZod8JaWia9KB2EVXdYrF", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about the basics of quantum computing. Assistant 1 gave a brief overview of quantum computing, its potential, and its applications. Assistant 2 provided a more detailed response, explaining the concept of qubits and different approaches to building quantum computers. Assistant 2's response was more comprehensive, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "PK7fcxBPUfD9DPqSiZd8an", "question_id": 6, "answer1_id": "fpRdMTdnfirosQixuf2Gez", "answer2_id": "WXRCqF34f4UUJzd3xbgAqT", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about the differences between plant-based and animal-based protein sources. Assistant 1 focused on the nutritional aspects, such as fat, calories, cholesterol, and resource usage. Assistant 2 provided a more detailed response, discussing nutritional value, absorption, sustainability, health effects, ethical considerations, and cost. Assistant 2's answer is more comprehensive and covers a wider range of aspects, which is why it receives a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "2cPJ5uF4r6z4EWKucgUdxs", "question_id": 7, "answer1_id": "PvGmsCJSNFcvQKmPTnnd7s", "answer2_id": "JREJbG5ZKXCNMoWoiJQxbC", "text": "8 10\nBoth Assistant 1 and Assistant 2 provided helpful and relevant answers to the question about developing critical thinking skills. Assistant 1 gave a brief overview of what critical thinking involves, which is useful for understanding the concept. However, Assistant 2 provided a more detailed and comprehensive list of 10 tips for improving critical thinking skills, making it a more valuable response for someone looking to develop these skills. Assistant 2's answer also covered a wider range of strategies, such as active listening, seeking diverse viewpoints, and practicing mindfulness, which contributes to its higher score.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "2P68gHgTycYPveTkXFmJ2V", "question_id": 8, "answer1_id": "n4ANAbpR3gvLPP8poPfKZ6", "answer2_id": "mmVwmX6TGJ2Y72gCNac4EQ", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about the challenges faced by the education sector today. Assistant 1's response was more concise, but it still covered a good range of challenges. Assistant 2's response was more detailed and organized, presenting the challenges in a numbered list format, which made it easier to understand and follow. Assistant 2 also touched on some additional aspects, such as accountability and assessment, and sustainability, which added more depth to the answer. Therefore, Assistant 2 receives a slightly higher score due to the better organization and additional details provided.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "KT5tYQWeruK84zYBEDifhA", "question_id": 9, "answer1_id": "STJ36GrgQMcaUi7zaoNPit", "answer2_id": "DMTZyzd4rRAFV43xtBJ9ns", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information regarding the primary factors that influence consumer behavior. Assistant 1 mentioned cultural, social, and personal factors, as well as advertising, marketing, and price. Assistant 2 provided a more detailed response, breaking down the factors into six categories: personal, psychological, social, economic, marketing, and product/service factors. Assistant 2's answer was more comprehensive and organized, which is why it received a slightly higher score. However, both responses were informative and useful.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "MAomLn7rTvxsZfGpv37ijQ", "question_id": 10, "answer1_id": "425SwYvqKPAXFGTYKXB7Cs", "answer2_id": "dETAsj4xHnUCSTkZezz8aM", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question about effective strategies for conflict resolution in the workplace. Both responses included a list of strategies with clear explanations, making it easy for the user to understand and apply the information. The level of detail in both responses was appropriate and informative. The slight difference in the strategies listed by each assistant does not significantly impact the overall quality of the answers, as both provided valuable insights and covered the main aspects of conflict resolution.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "di5wzaNZCApV85kfJyKtGH", "question_id": 11, "answer1_id": "VbNAuj6KAkMdLJQXMo22oK", "answer2_id": "C8ksZxg3LshMUWiLxPanbt", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information regarding the implications of using single-use plastic bottles versus reusable bottles. Assistant 1 focused more on the environmental aspects and briefly touched on human health, while Assistant 2 provided a more balanced view of both environmental and health impacts. Assistant 2 also organized the information more clearly, making it easier to understand the different implications. Both assistants provided a good level of detail, but Assistant 2's response was slightly more comprehensive, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "FCat6rmvhMiL5B8DJdKysU", "question_id": 12, "answer1_id": "CNGqAeu2QJbQ4QGzHJDPdq", "answer2_id": "NeHhRc5P5uAU8eWSJBRkhG", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant information in response to the question about designing an inclusive and accessible public transportation system. Assistant 2's answer was slightly more detailed and organized, with a numbered list of factors to consider, which made it easier to follow and understand. Assistant 1 mentioned the integration with other services, which is an important aspect that Assistant 2 did not mention. However, Assistant 2 provided more specific examples of accessibility features and emphasized the importance of customer service, information and communication, and affordability, which are crucial factors in designing an inclusive public transportation system. Overall, both assistants provided valuable information, but Assistant 2's response was more comprehensive and well-structured.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "hg92jQt3a8qPSVTLESQmbh", "question_id": 13, "answer1_id": "E8w2qYqnm8iqCrSkUv62sz", "answer2_id": "KAJ7UVwu8oCKyxZj9j82pm", "text": "8 10\nBoth assistants provided helpful, relevant, and accurate information about how governments can use fiscal and monetary policies to combat economic recessions. However, Assistant 2 provided a more detailed and structured response, with specific examples and a clear distinction between fiscal and monetary policies. Assistant 1's response was more general and less detailed, which is why Assistant 2 receives a higher score.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "6WZVJUT39icJDPALuZRbUN", "question_id": 14, "answer1_id": "8o5yMymfzo6kzmp9GK5MWr", "answer2_id": "NnWfaeRe8PmitgmV4u5fY8", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a general overview of the issue and suggested ways to overcome language and cultural barriers. However, Assistant 2 provided a more detailed response, outlining specific ways in which these barriers can affect communication and relationships, such as language differences, cultural norms, stereotypes, prejudice, and power dynamics. This additional detail and structure make Assistant 2's response slightly more informative and comprehensive, resulting in a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "8kChSLEztqMSdQkV9HDtMw", "question_id": 15, "answer1_id": "kbJVEEsdsSScEq5Y5furr7", "answer2_id": "WiGpqKRRwWonwgU95piNNc", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 focused on a variety of ways AI can be used in healthcare, such as assisting with diagnoses, analyzing lab results, automating administrative tasks, and providing virtual health coaching. Assistant 2, on the other hand, provided a more detailed response, discussing the use of AI in analyzing patient data, automating routine tasks, remote patient monitoring, personalized treatment plans, and medical research. Assistant 2's answer was more comprehensive and provided a better understanding of the potential impact of AI on healthcare delivery, which is why it received a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "JQCpdYBgdJcDDVXWNgNAf8", "question_id": 16, "answer1_id": "CMUL5ULZuR7YC5EPzCBN2N", "answer2_id": "iangiZeex5ndxAXnWMrxBW", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about CRISPR-Cas9 technology, its potential applications, and ethical implications. Assistant 2, however, provided a more detailed response, including a clearer explanation of the gene editing process and the specific repair mechanisms involved (HDR and NHR). Assistant 2 also discussed a wider range of potential applications and ethical concerns. While Assistant 1's response was informative, Assistant 2's response was more comprehensive and in-depth, which is why Assistant 2 received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "VzPqpgnivGDdXhWdxQyvvH", "question_id": 17, "answer1_id": "kEmDDQyNqSkyFihYEEBpuR", "answer2_id": "XnMRLphzYQX4QRNht7tbui", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about vaccinations and herd immunity. Assistant 1 gave a brief overview of how vaccinations work and the concept of herd immunity. Assistant 2 provided a more detailed explanation of the immune response triggered by vaccinations and the importance of herd immunity for vulnerable populations. Assistant 2 also mentioned the critical threshold for achieving herd immunity and the benefits of vaccination for the community. Therefore, Assistant 2 receives a slightly higher score due to the additional details and clarity provided in the response.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "DjcVQrARdkz8zZU4ahzuJb", "question_id": 18, "answer1_id": "Qs3grQsqFVGK9EVkCkf9PB", "answer2_id": "HZc37bwy646mRzbqSsDAob", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question. Assistant 1 gave a concise overview of the influence of social media platforms on news consumption and the potential implications for the spread of misinformation. However, Assistant 2 provided a more detailed response, outlining specific ways in which social media platforms influence news consumption and sharing, such as personalization, virality, amplification, filter bubbles, confirmation bias, and lack of fact-checking. This additional detail and organization make Assistant 2's response slightly more informative and comprehensive, resulting in a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "eHLHXtjjeVUMsFLeAoQtbM", "question_id": 19, "answer1_id": "kzZ6dKN7hkRWjqtdHr7Qns", "answer2_id": "iJrMatLrMdJyyqMx9uJ45a", "text": "8 9\nBoth assistants provided helpful, relevant, and accurate information regarding the influence of cultural, social, and economic factors on people's food choices and how this knowledge can be used to promote healthier diets. Assistant 2, however, provided a more detailed and structured response, with clear examples for each factor, making it easier to understand the different influences. Assistant 1's response was also informative, but it lacked the clear organization and specific examples that Assistant 2 provided.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "5BcjGdUzPQbMD5MKmAvtRR", "question_id": 20, "answer1_id": "DPPDG6YGFJij2GCmRL66PU", "answer2_id": "oVEHqDnDTEADZSFfKgFTZd", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a brief but clear explanation of natural selection and its role in evolution and adaptation. Assistant 2, however, provided a more detailed response, breaking down the process of natural selection into five steps and explaining each step's contribution to evolution and adaptation. This additional detail and organization make Assistant 2's answer slightly more informative and comprehensive, resulting in a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "XpFSu84sZ8tACx9WkBygF5", "question_id": 21, "answer1_id": "D62FjDb4nZANzPpfSfsiyn", "answer2_id": "WLAj4u59bj2oEXzahF79ek", "text": "7 9\nAssistant 1 provided a brief and general introduction, while Assistant 2 offered a more detailed and immersive response, which better captured the essence of a medieval knight's introduction at a royal banquet. Assistant 2's response included a specific speech, demonstrating a deeper understanding of the context and the expectations of the situation.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "eqRG5G2adk4SQNsppwVVW6", "question_id": 22, "answer1_id": "k7E4NNw5kyj9DmvP5Pu2zb", "answer2_id": "fJPnM2XcRveW2zR4DDaeTb", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided relevant and engaging speeches to motivate a pirate crew to search for hidden treasure. Assistant 1's response was shorter and more focused on the excitement of the adventure, while Assistant 2's response was more detailed, providing a context for the speech and emphasizing the challenges and rewards of the journey. Assistant 2's response was slightly better due to its more comprehensive approach and the inclusion of a clear goal for the crew.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "XU7RnpgdvubdNHZ8ryeBNE", "question_id": 23, "answer1_id": "KFocjVCejYrU3YmLjAqoUF", "answer2_id": "fY4Xed6veWpcKfj5krZz8m", "text": "8 9\nBoth assistants provided relevant and creative responses to the question. Assistant 1 gave a general description of how a Shakespearean character would declare their love, which was helpful and accurate. Assistant 2 went a step further by providing an actual example of a soliloquy, making it more engaging and detailed. Therefore, Assistant 2 receives a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "64ayLmABqYNLkAVAj2MSrF", "question_id": 24, "answer1_id": "dq8Sm9djS7e7y9sG9vmMJf", "answer2_id": "LqFJA2JQbBXP77nkYjtrZK", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the user's question. Assistant 1 gave a more traditional superhero origin story, explaining that they were born with special abilities and learned to use them for good. Assistant 2, on the other hand, provided a unique origin story as an advanced artificial intelligence created by scientists. Both answers were detailed and engaging, but Assistant 2's response was slightly more detailed and creative, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "cfBjbHjZsP9rKVXVxEaZoC", "question_id": 25, "answer1_id": "XZ8fG8e6u7CyKd2moK6abe", "answer2_id": "WxCKcRstJPXTXnqEzSX3Hg", "text": "8 10\nBoth Assistant 1 and Assistant 2 provided relevant and accurate information in response to the user's question. However, Assistant 2's answer was more detailed and comprehensive, covering a wider range of technological advancements from various fields, such as fusion power, nanotechnology, artificial intelligence, space exploration, quantum computing, and biotechnology. Assistant 1 mentioned some general advancements like time travel, intelligent robots, autonomous vehicles, virtual reality, augmented reality, artificial intelligence, and machine learning, but did not provide specific examples or details. Therefore, Assistant 2 receives a higher score of 10, while Assistant 1 receives an 8.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "aoxUcPU7Z3swngyhGAsfrc", "question_id": 26, "answer1_id": "oKaXHfoK4pXwrefFWXmeA8", "answer2_id": "dgPJ7DvtFHD7mxtRwzM3vW", "text": "8 10\nAssistant 1 provided a brief but relevant response, describing the winning play in a simple manner. However, the answer lacked detail and excitement that would be expected from a sports commentator. Assistant 2, on the other hand, delivered a more engaging and detailed response, capturing the excitement and tension of the final moments of the game. The answer provided a vivid picture of the winning play, the players involved, and the emotions of both teams, making it a more immersive and satisfying response.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "RPyrLb5gh3NCxy5HhUu3Qy", "question_id": 27, "answer1_id": "ZwiZfvDWm7SETKNBfDk7Mb", "answer2_id": "ADX83sWvjJkewJX6JmYUzQ", "text": "8 10\nAssistant 1 provided a brief and vague description of the signature dish, which did not give a clear idea of what the dish is or its ingredients. The response was relevant but lacked detail and creativity. Assistant 2, on the other hand, provided a detailed, creative, and engaging description of the signature dish, including the name of the dish, the ingredients, the flavors, and the presentation. Assistant 2's response was more helpful, relevant, accurate, and detailed, which is why it received a higher score.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "2hn8AqjvpXzHXKu2P69mco", "question_id": 28, "answer1_id": "DxYopRe2LcTJMy3FWu6btd", "answer2_id": "ihNG3rwsrt95NDhCAFeSDR", "text": "8 9\nBoth assistants provided relevant and detailed responses to the question. Assistant 1 focused on describing the emotions and the view from the top, which directly addressed the user's question. Assistant 2, however, went a step further by acknowledging its AI nature and providing a more comprehensive response, including the importance of proper training, experience, and equipment. This additional information is valuable for someone interested in mountain climbing. Assistant 1's response was good, but Assistant 2's response was more informative and well-rounded, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "QKzMYoFj48wZJPVjZnXD4V", "question_id": 29, "answer1_id": "WC3UJVh4jQ5RUkpcRMU98L", "answer2_id": "Gmhqf3z4LvVfwPNFJ89BKd", "text": "8 9\nBoth assistants provided relevant and helpful answers, but Assistant 2's response was more detailed and organized. Assistant 1 briefly mentioned the challenges faced, while Assistant 2 provided a step-by-step description of daily life on Mars and elaborated on the challenges. Assistant 2's answer also touched upon the importance of communication with Earth and the psychological aspect of living on another planet, making it a more comprehensive response.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "F4eWAVuERss6hdsTXDT43V", "question_id": 30, "answer1_id": "gTvgn6ksDjGGgdprw6AG5A", "answer2_id": "gSwkKJCn6qDnNZond2xVJ3", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided relevant and detailed responses to the user's question. Assistant 1 described forming an alliance with other survivors, sharing knowledge and skills, and working together to stay alive. Assistant 2 went into more depth about the daily struggles, the process of learning new skills, and the importance of forming alliances with like-minded individuals. Assistant 2 also mentioned the need for caution when encountering dangerous characters and the determination to rebuild society. While both responses were helpful and accurate, Assistant 2 provided a more comprehensive and engaging answer, which is why it received a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "5T23NeQWsoTreXFBErzMfH", "question_id": 31, "answer1_id": "3q7giCk2BA3Ye4Tm9HC2iw", "answer2_id": "8RaBeMjxx2bCp2GKWv7YiP", "text": "8 10\nAssistant 1 provided a decent response, but there was an error in the last sentence, stating that higher prices could indicate popularity among locals, which is not necessarily true. Assistant 2, on the other hand, provided a more detailed and accurate response, covering various aspects of how to determine the popularity of a restaurant among locals or tourists, and also explained why this information might be useful. Assistant 2's response was more comprehensive and well-structured, making it easier to understand and follow.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "D4k3jKh84j9z9Vtpm3Emvw", "question_id": 32, "answer1_id": "hRGsxy86v26SC4yAQS29X4", "answer2_id": "C65PZkmAfFfWRs4bPhyKqg", "text": "7 9\nAssistant 1 provided a few clues that suggest someone is pretending to understand a topic, but their answer was not as detailed or comprehensive as Assistant 2's response. Assistant 2 provided a more extensive list of subtle clues, each with a clear explanation, making their answer more helpful and informative. Both answers were relevant and accurate, but Assistant 2's response was more detailed and precise, which is why it received a higher score.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "bes2VMcdsy6n47zpvsiXGs", "question_id": 33, "answer1_id": "3n49A5ggJERfXYrLns3ZeU", "answer2_id": "4so4HTEjgDZKTqNAgkHHQX", "text": "8 10\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. However, Assistant 2's response was more detailed and comprehensive, covering a wider range of reasons why someone might choose to use a paper map or ask for directions instead of relying on a GPS device or smartphone app. Assistant 1's answer was still useful and touched on some key points, but it lacked the depth and elaboration that Assistant 2's response provided.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "2TkHUHRd2MeXpUgXUHHKFe", "question_id": 34, "answer1_id": "ErCpFtPuYVru4oTTk4WrxG", "answer2_id": "FCYaiexEzdoLFPAwvTgDDm", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant answers to the question. Assistant 1 focused on body language, eye contact, and engagement in the conversation as indicators of genuine interest. Assistant 2 provided a more detailed response, listing five specific clues to look for, including active listening, engaged body language, personal investment, authenticity, and follow-up. Both answers were accurate and relevant, but Assistant 2's response was more comprehensive and provided a slightly higher level of detail, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "LrvxJCFQDLW2c29FpmG9Xp", "question_id": 35, "answer1_id": "PTNoCRMZWoJk8HaKX7fW45", "answer2_id": "76EPQDh4ZNxBMGqED9LEFi", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a good general overview of the benefits of shopping at small, locally-owned businesses, mentioning community support, personal experience, quality products, and local culture. Assistant 2, however, provided a more detailed and organized response, listing specific reasons and elaborating on each point. This made Assistant 2's answer slightly more informative and comprehensive, earning it a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "L25o9xkc8WhLLtG82XrVHc", "question_id": 36, "answer1_id": "n8cFs9KENNwZ4z3SR4iXTr", "answer2_id": "cvBg3gyCyDuyESof3YXhTE", "text": "7 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant information on assessing the credibility of a source. However, Assistant 2's response was more detailed and precise, covering a wider range of factors to consider, such as objectivity, date of publication, and skepticism. Assistant 1's response was accurate but lacked the depth and comprehensiveness of Assistant 2's answer. Therefore, Assistant 2 receives a higher score due to its more thorough and well-rounded response.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "YXjoGG6fkh6RzQaxpscw7u", "question_id": 37, "answer1_id": "GzxL9mmEK5RzKqRbqBMUVC", "answer2_id": "kRgfUJ7qqkyZUnLd2fnnaX", "text": "8 10\nBoth Assistant 1 and Assistant 2 provided relevant and accurate answers to the question. Assistant 1's response was helpful and touched on the main idea that people have different preferences for thrilling activities. However, Assistant 2's response was more detailed and comprehensive, offering various factors that can influence why some people enjoy being scared while others avoid it. Assistant 2's answer also delved into the complexity of the interplay between biological, psychological, and environmental factors, making it a more informative and well-rounded response.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "fCgyimZZk3m5nMi3XaoEU9", "question_id": 38, "answer1_id": "QpoHFgb9SzwuaXQQUuBUQD", "answer2_id": "J3YuizKcHQ74ydNyCcwgwu", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 focused on the importance of observing interactions, addressing, handling disagreements, problem-solving, and nonverbal cues to understand cultural norms. Assistant 2 emphasized the learning aspect of culture through social interactions, the importance of observing appropriate and inappropriate behaviors, and the reactions and responses of others. Assistant 2's response was slightly more detailed and provided a clearer example, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "FeNNbc5tyYVh6RD8QGx9U5", "question_id": 39, "answer1_id": "Fxe6MS4GpP3LMDUwzY2cPA", "answer2_id": "abWLpFojLpNPfDGHpuRSUG", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 briefly presented both sides of the argument, allowing the reader to understand the main points of the debate. However, Assistant 2 went into more detail, providing specific points to consider when forming an opinion on the topic, and discussing the benefits and risks of both space exploration and addressing Earth's problems. This additional information makes Assistant 2's response more comprehensive and informative, resulting in a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "K3bVpZDV4T29mFFZneZnFv", "question_id": 40, "answer1_id": "mJiQ2FGR4Xb8kmhZjharkw", "answer2_id": "Ki4fkJvsoSxuQeSoj2AcBG", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question. Assistant 1 emphasized the importance of striking a balance between job creation and technological progress and suggested policies and initiatives to promote both. Assistant 2 also emphasized the need for balance but provided a more detailed explanation of the potential impacts of automation on jobs and the economy, as well as the benefits of technological progress. Assistant 2's response was more comprehensive, which is why it received a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "8QQXLYPzxkhj3UvjehmJ3a", "question_id": 41, "answer1_id": "6Kph4RHRKEZ4YUoaHuEhBv", "answer2_id": "GRQjYgAapNAVqzuZR4KQpf", "text": "7 6\nAssistant 1 provided a more accurate and detailed response, explaining the purpose of blinking and giving a clear estimate of 50 million blinks in a lifetime. However, the response could have been improved by breaking down the calculation step-by-step. Assistant 2 provided a step-by-step calculation, but the blink rate used was incorrect, leading to an inaccurate estimate of 4,996,800 blinks in a lifetime. Additionally, Assistant 2 incorrectly stated that the blink rate during sleep is the same as when awake, which is not true. Overall, Assistant 1's response was more helpful, relevant, and accurate, while Assistant 2's response had some inaccuracies and a lower level of detail.", "score": [7.0, 6.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "hLQwp4DchSxBwsWUUBMYmM", "question_id": 42, "answer1_id": "WBwpBQwhxn5kxLDb7MschC", "answer2_id": "SB5a2AiK224hB927vkqvYs", "text": "4 9\nAssistant 1 provided an incorrect and confusing answer, stating that a grain of salt contains 102.98 atoms, which is not a reasonable number for atoms in a grain of salt. The explanation provided was also incorrect and did not make sense. On the other hand, Assistant 2 provided a detailed and step-by-step explanation, estimating the number of atoms in a grain of salt based on the average size of a grain of table salt and using sodium chloride as an example. The calculations were clear and easy to follow, resulting in an estimate of approximately 7.13 x 10^27 atoms in a grain of table salt with a diameter of 50 \u00b5m. This response was helpful, relevant, accurate, and provided a sufficient level of detail.", "score": [4.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Cvgm9KPXmNDHoT7HZ3nKnA", "question_id": 43, "answer1_id": "kf8nahQVci2ZLaYikagB7U", "answer2_id": "4XYycBrMiJgYKPof2P6xoe", "text": "6 9\nAssistant 1 provided an incorrect number of lightning strikes per day (2000) and did not give a clear step-by-step explanation as requested. Assistant 2, on the other hand, provided a more accurate estimate (100,000,000) and took the reader through the reasoning process, discussing the factors that contribute to lightning strikes, such as electrical charge, weather conditions, and location. Assistant 2's response was more helpful, relevant, accurate, and detailed, which is why it received a higher score.", "score": [6.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "BQpXVvTLQ8DwU5PbhkjavA", "question_id": 44, "answer1_id": "Gptgryd4o2dC8V5aqRmeJJ", "answer2_id": "fpoXWHHdpv7XNBTS2NRY6d", "text": "6 8\nAssistant 1 provided an incorrect calculation and explanation, as the weight of the house was not accurate and the number of cubic feet of helium needed was not properly explained. Assistant 2, on the other hand, provided a more detailed and step-by-step explanation, acknowledging the unrealistic nature of the scenario and using a more reasonable weight for the house. Although both answers were not perfect, Assistant 2's response was more helpful, relevant, and accurate.", "score": [6.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "cpKEBBh27iBFMHF2DMhbmF", "question_id": 45, "answer1_id": "RfBWW8ZhdfTuTMb454Un4o", "answer2_id": "GRXWdnzLLzmeZRU67PMTb7", "text": "7 8\nAssistant 1 provided an answer with a specific number of text messages sent globally in a minute, but the source of the information is not mentioned, which makes it difficult to verify the accuracy of the data. The explanation also focused on the growth of text messages and the rise of instant messaging applications, but it didn't provide a step-by-step reasoning for the number provided.\n\nAssistant 2, on the other hand, acknowledged the difficulty in determining the exact number of text messages sent globally in a minute and provided a more detailed explanation of the reasons why it is challenging to track this information. Although Assistant 2 didn't provide a specific number, the response was more realistic and informative, explaining the complexity of text message communication.", "score": [7.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "GZtTjxWteggtdMXqBr4QZd", "question_id": 46, "answer1_id": "neGgLYm47JvqN8qkw8VeoW", "answer2_id": "RTxk2jYsjYiiWMwcRjmfwu", "text": "7 9\nAssistant 1 provided a rough estimate of 1 billion words spoken daily, but the explanation lacked a step-by-step reasoning and did not provide any sources or calculations to support the claim. Assistant 2, on the other hand, provided a more detailed step-by-step explanation, including an estimate of 100 billion words spoken daily, which was based on the world population and the average number of words spoken per person per day. Assistant 2 also acknowledged the limitations of the estimate and the factors that could influence the actual number. Therefore, Assistant 2's response was more helpful, relevant, accurate, and detailed compared to Assistant 1's response.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "nnPgYU9HHowARyLhxQKKwm", "question_id": 47, "answer1_id": "KSePbzLwsYasR3aui4HU8h", "answer2_id": "2J2Et6W8u2kXLTUgfYrPxe", "text": "6 8\nAssistant 1 provided a general explanation of snowflake formation and mentioned that the number of snowflakes can vary depending on location and storm severity. However, the answer lacked a step-by-step reasoning process and did not provide an estimate for the number of snowflakes during a typical winter. Assistant 2, on the other hand, provided a more detailed response, explaining the factors that influence snowflake formation and offering a rough estimate based on average conditions. Although the answer still did not provide an exact number, it gave a clearer understanding of the factors involved and the complexity of estimating the number of snowflakes in a typical winter.", "score": [6.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "CoqavHgbi2d4d9Xo9LWGZ5", "question_id": 48, "answer1_id": "SWWfLpP2gnWHLbYRZXNsW3", "answer2_id": "nSGoG9Z5g5VuCXgmQJJKrq", "text": "7 8\nAssistant 1 provided an estimate of 100 billion pages based on 130 million unique titles and an average of 200 pages per book. The answer was relevant and informative, but the source of the data was not mentioned, which affects the credibility of the information. Assistant 2, on the other hand, acknowledged the impossibility of providing an exact number and explained the reasoning behind their estimate. They used 13 million books and an average of 250-300 pages per book, resulting in an estimate of 3.25 billion pages. Assistant 2's answer was more detailed and transparent in their approach, which makes their response more helpful and reliable. However, both assistants provided different estimates, which may cause confusion. Assistant 2's response was slightly better due to the clarity in their reasoning, but both could improve by providing more accurate and up-to-date data.", "score": [7.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "MZLyQgMwXpVnFGWJxPjLU7", "question_id": 49, "answer1_id": "WaBwKYhs7eAG22qCGLH2j3", "answer2_id": "ScqJdUq9n5bp9qPv5WPqG5", "text": "6 8\nAssistant 1 provided a response that was relevant and somewhat helpful, but the calculation was incorrect and the answer lacked detail. The assistant multiplied the number of years by the length of a year, which is not the correct way to calculate the number of orbits. Assistant 2, on the other hand, provided a more detailed and accurate response, taking into account the age of the Earth and the elliptical nature of its orbit. The explanation was clearer and more precise, leading to a better understanding of the reasoning behind the estimate. However, both assistants could have mentioned that the exact timing of the emergence of life on Earth is uncertain, which would affect the final estimate.", "score": [6.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "ZgP6B6jZ2sgd8f6aDh3zLo", "question_id": 50, "answer1_id": "MfMJeE9om7qyBbqopHouf4", "answer2_id": "GdLFr88pCwsGpfRBRQQkyh", "text": "7 9\nAssistant 1 provided a conservative estimate of several hundred thousand songs recorded throughout history, but the answer lacked depth and detail. Assistant 2, on the other hand, provided a more comprehensive response, discussing the history of music, the invention of recording technology, and the rise of digital music. Assistant 2 also acknowledged the difficulty in estimating the exact number of songs and suggested that there could be millions or even billions of songs recorded. This answer was more informative and took the reader through the reasoning step-by-step, which is why Assistant 2 receives a higher score.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "3hFbcLp9xWWFD78soe4nEY", "question_id": 51, "answer1_id": "TjWPRDM6JFpPF8xeRptCKb", "answer2_id": "Sa7uNEbFGRFuXBAwau8sHS", "text": "7 9\nAssistant 1 provided a brief response, mentioning that the Internet would have been primarily used by the wealthy and powerful and that it would have been slower and more expensive. However, the answer lacked depth and context. Assistant 2, on the other hand, provided a more detailed and thoughtful response, discussing the technological and cultural context of the Renaissance period and how it might have influenced the development of the Internet. Assistant 2 also considered the potential limitations of the technology at the time and how it would have affected the Internet's evolution. Overall, Assistant 2's response was more helpful, relevant, and accurate, with a higher level of detail.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "PVxq9EuwZoGbUUbWBh5bi4", "question_id": 52, "answer1_id": "iR2tYTsWTFENEP7Qy9RgtX", "answer2_id": "T6Ar3cAEw3AmVVQTcCPp8N", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 focused more on the cultural aspects and the potential for the Aztecs to maintain their traditional customs, beliefs, and languages. Assistant 2 provided a more detailed response, discussing the potential impact on the Aztec civilization, the spread of European diseases, the economy, and the possibility of forming alliances with other indigenous groups. Assistant 2's answer was more comprehensive, which is why it received a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "2JxUhEFw64P59ZWvNWk5eH", "question_id": 53, "answer1_id": "AZdS8xAi3GwAmCqkNSnnwv", "answer2_id": "KiZQev5JEk2h6JYeQnFmtM", "text": "7 9\nBoth assistants provided relevant and accurate information about the potential consequences of the Black Death not occurring in the 14th century. Assistant 2, however, offered a more detailed and balanced analysis of the possible outcomes, discussing both positive and negative aspects, as well as acknowledging the difficulty in predicting the exact course of history. Assistant 1's response was more speculative and focused on the positive outcomes, such as the Renaissance and scientific revolution occurring earlier. Overall, Assistant 2 provided a more comprehensive and nuanced response, which is why it received a higher score.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Y5QuvZeyyEXuBwBLmxqFVA", "question_id": 54, "answer1_id": "VmwifF2JD5osYKDTqv2ZRS", "answer2_id": "cYiyYKKXM3GXkrZHAbX83S", "text": "7 8\nBoth Assistant 1 and Assistant 2 provided relevant and accurate responses to the question. Assistant 1 focused on the potential contributions Newton could have made in the field of biology, such as studying the human body and animal behavior. However, Assistant 2 provided a more comprehensive response, discussing Newton's actual contributions to various fields and acknowledging the difficulty in predicting his specific contributions to biology. Assistant 2's response was more detailed and balanced, which is why it received a higher score.", "score": [7.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "DZ7peVvCwPsXCtHAtyJtwP", "question_id": 55, "answer1_id": "mUL5UPj3qDGaCriEjL2U3B", "answer2_id": "PQmMUdAAcBsAWmWaTvdHSU", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant answers to the question. Assistant 1 gave a brief overview of the potential impact on the music world and the cultural influence of the Beatles. Assistant 2 went into more detail, listing several possible outcomes if the Beatles had never formed as a band. While both answers were accurate and relevant, Assistant 2's response was more detailed and provided a more comprehensive exploration of the hypothetical scenario, which is why it received a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "6LfJJ8Yn6gcnrNQETUo3fm", "question_id": 56, "answer1_id": "dVdwUoVrAQJDuWxiodykiw", "answer2_id": "PorExChQ9VeYsPJptdgtsB", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided relevant and accurate answers to the question. Assistant 1 gave a brief but clear response, mentioning the critical advantage gained by the Allies due to cracking the Enigma code. Assistant 2, however, provided a more detailed response, discussing the potential consequences of not cracking the code, such as the development of alternative strategies or technologies. Assistant 2 also acknowledged the difficulty in predicting the exact outcome without Turing's contributions. Therefore, Assistant 2 receives a slightly higher score for providing a more comprehensive answer.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "SA89EZJJozceMFCjAp36JK", "question_id": 57, "answer1_id": "EiNn9jjfy7dga6xfCtLtF8", "answer2_id": "249f6dSMwZRZVMmtxv6yDm", "text": "8 9\nBoth assistants provided helpful, relevant, and accurate information about the implications of the Suez Canal not being constructed. Assistant 1 focused more on the impact on international trade and navigation, while Assistant 2 expanded on the historical, political, and technological aspects of the canal's construction. Assistant 2's response was slightly more detailed and provided a broader perspective on the topic, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "ZqQyfNvvEcnpPwJk3J2Uai", "question_id": 58, "answer1_id": "eqG9f2R9hXVyZrZMpcqAYq", "answer2_id": "nxa3m6kiAZwKgcMUBY8KYz", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a brief overview of the possible outcomes if the Maya civilization had not collapsed, mentioning the potential for continued growth in various areas. Assistant 2, however, provided a more detailed response, discussing the potential impact on the development of other civilizations, the possibility of further scientific and technological advancements, and the potential changes to the political and cultural landscape in Mesoamerica. While both answers were informative, Assistant 2's response was more comprehensive and detailed, which is why it received a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "U4AYzQWkwxdSDQT7aCEjHU", "question_id": 59, "answer1_id": "ex42CLEzDVC2TxAvMCtYQJ", "answer2_id": "DXFvhjCaKqQiBsFDCkXGMT", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant answers to the question. Assistant 1 briefly mentioned the possible consequences of Columbus not discovering the Americas, such as the indigenous people living in relative isolation and the delay of European colonization. Assistant 2, however, provided a more detailed response, discussing the potential for the indigenous peoples to thrive and develop without outside influence, as well as the possibility of other European explorers eventually discovering the Americas. Assistant 2's answer also touched on the profound impact of Columbus's discovery on the world. Both answers were accurate and relevant, but Assistant 2's response was more comprehensive and detailed, earning it a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "PfbYXoERxbzzmrhe3K6gfH", "question_id": 60, "answer1_id": "RfFANSwHeCm3Pqe2AJ86Dk", "answer2_id": "BCUK5VcpZK26jMJ2UMgR3E", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant answers to the question. Assistant 1 focused on the potential benefits of success for van Gogh, such as recognition, financial stability, and opportunities for collaboration. Assistant 2, on the other hand, provided a more detailed response, discussing the potential impact on his art, the possibility of exploring new techniques, and the pressures that might have come with fame. Both answers are accurate and relevant, but Assistant 2's response is slightly more detailed and comprehensive, which is why it receives a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "S76jaMcti5vwnHtJqAW6zb", "question_id": 61, "answer1_id": "nzxdtWmgQhRkHeVAanVogZ", "answer2_id": "JHTKBrLVTp7bv5zW2uwYVW", "text": "6 9\n\nAssistant 1 provided a general description of the program but did not provide any code implementation. The description is clear and concise, but it lacks the actual code to solve the problem.\n\nAssistant 2 provided a complete C++ code implementation that reads a text file line by line and counts the number of occurrences of a specific word in the file. The code is well-structured, readable, and includes helpful comments. However, the program only checks if the search string is present in the line, not the exact number of occurrences of the word in the line. To improve the code, Assistant 2 could implement a more precise word counting mechanism that accounts for multiple occurrences of the search string within a single line.\n\nHere's an improved version of Assistant 2's code that counts the exact number of occurrences of the word in the file:\n\n```cpp\n#include <iostream>\n#include <fstream>\n#include <string>\n#include <sstream>\n\nusing namespace std;\n\nint main()\n{\n    // Specify the name of the text file you want to read\n    string filename = \"example.txt\";\n\n    // Open the file in binary mode for reading\n    ifstream file(filename, ios::binary);\n\n    // Set the string to search for\n    string search_string = \"example\";\n\n    // Initialize a counter to keep track of the number of occurrences of the search string\n    int counter = 0;\n\n    // Start reading the file line by line\n    string line;\n    while (getline(file, line))\n    {\n        // Create a stringstream to read words from the line\n        stringstream ss(line);\n        string word;\n\n        // Read words from the line\n        while (ss >> word)\n        {\n            // Check if the word matches the search string\n            if (word == search_string)\n            {\n                // Increment the counter if the word matches the search string\n                counter++;\n            }\n        }\n    }\n\n    // Close the file\n    file.close();\n\n    // Print the number of occurrences of the search string\n    cout << \"Number of occurrences of search string: \" << counter << endl;\n\n    return 0;\n}\n```\n\nThis improved version uses a `stringstream` to read words from each line and compares each word to the search string. If the word matches the search string, the counter is incremented. This ensures that the program counts the exact number of occurrences of the word in the file.", "score": [6.0, 9.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "72aGqhr2T2BS7oC25BsQoc", "question_id": 62, "answer1_id": "kRo6z5qmeiSM8Xz6BPJHLC", "answer2_id": "jyzD2deb9JAffRhhkk37r5", "text": "6 4\n\nAssistant 1:\nStrengths:\n- The code is well-commented and easy to understand.\n- The function signature is clear and includes type hints for the input parameters.\n\nWeaknesses:\n- The implementation is incorrect. The logic for updating the `results` matrix is not correct for the longest common subsequence problem.\n- The code initializes the first row and column of the `results` matrix to 0 twice, which is redundant.\n\nSuggestions for improvement:\n- Correct the logic for updating the `results` matrix. When s1[i-1] == s2[j-1], the value should be results[i-1][j-1] + 1. When s1[i-1] != s2[j-1], the value should be max(results[i-1][j], results[i][j-1]).\n- Remove the redundant initialization of the first row and column of the `results` matrix.\n\nAssistant 2:\nStrengths:\n- The code is well-structured and easy to read.\n\nWeaknesses:\n- The implementation is incorrect. The logic for updating the `dp` matrix is not correct for the longest common subsequence problem.\n- The code initializes the first row and column of the `dp` matrix to `float('inf')`, which is not appropriate for the problem. They should be initialized to 0.\n- The code does not include comments explaining the logic and functionality.\n\nSuggestions for improvement:\n- Correct the logic for updating the `dp` matrix. When str1[i-1] == str2[j-1], the value should be dp[i-1][j-1] + 1. When str1[i-1] != str2[j-1], the value should be max(dp[i-1][j], dp[i][j-1]).\n- Initialize the first row and column of the `dp` matrix to 0.\n- Add comments to the code to explain the logic and functionality.", "score": [6.0, 4.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "jadrVtHskPRvbZmHqZkVRE", "question_id": 63, "answer1_id": "7kj8odEE79UBdR4pT6u6TY", "answer2_id": "jPGHEfp7FxhDyvRA6qEN3j", "text": "7 9\n\nAssistant 1:\nStrengths:\n- Provided a valid regular expression for email validation.\n\nWeaknesses:\n- Did not provide a complete Python implementation.\n- No comments or explanation of the regular expression components.\n\nSuggestions for improvement:\n- Provide a complete Python implementation using the `re` module.\n- Add comments to explain the different parts of the regular expression.\n\nAssistant 2:\nStrengths:\n- Provided a complete Python implementation using the `re` module.\n- Included a clear and concise explanation of the regular expression components.\n- Properly tested the regular expression with a sample email address.\n\nWeaknesses:\n- The explanation of the regular expression components is slightly different from the actual regular expression used in the code.\n\nSuggestions for improvement:\n- Ensure that the explanation of the regular expression components matches the actual regular expression used in the code.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "J5F2uLKW8H38af5Xx2dBqo", "question_id": 64, "answer1_id": "UULZ4GLz9j9ot7tN7x3ySD", "answer2_id": "Ra9eTcAuNZPkPRnaHiQrak", "text": "4 6\n\nAssistant 1:\nStrengths:\n- The explanation of the logic is clear and easy to understand.\n\nWeaknesses:\n- The provided code is not in any programming language, it's just a description of the algorithm.\n- The algorithm itself is incorrect and doesn't use dynamic programming.\n- There are no comments in the code.\n\nSuggestions for improvement:\n- Provide actual code in a specific programming language.\n- Use a correct dynamic programming approach for solving the problem.\n- Add comments to the code to explain the logic and functionality.\n\nAssistant 2:\nStrengths:\n- The code is provided in Python, which is a widely used programming language.\n- The code is structured and easy to read.\n\nWeaknesses:\n- The code does not use dynamic programming, it uses recursion instead.\n- The memoization table is not used, and the code will be inefficient for large values of n.\n- The comments are not very helpful in explaining the logic and functionality of the code.\n\nSuggestions for improvement:\n- Implement a dynamic programming approach, such as using a bottom-up approach with a memoization table.\n- Use the memoization table to store the results of previous calculations to avoid redundant calculations.\n- Improve the comments to better explain the logic and functionality of the code.", "score": [4.0, 6.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "bBz3M9u9WMW5o9Qz8CELFx", "question_id": 65, "answer1_id": "Rh8P3bxSJx4p6nCZkSZBrh", "answer2_id": "5mbEFLEnEx8Cm2wEF8WAbM", "text": "8 10\n\nAssistant 1:\nStrengths:\n- Provides a clear explanation of how the binary search algorithm works.\n- Explains the process of repeatedly splitting the array and comparing the middle element.\n\nWeaknesses:\n- Does not provide an actual code implementation of the binary search algorithm.\n- Lacks examples or comments to help the reader understand the algorithm better.\n\nSuggestions for improvement:\n- Provide a code implementation of the binary search algorithm in a programming language.\n- Include examples and comments to help the reader understand the code and its functionality.\n\nAssistant 2:\nStrengths:\n- Provides a complete and accurate implementation of the binary search algorithm in Python.\n- Includes a clear example of how to use the function with a sorted array and a target value.\n- The code is well-structured, readable, and efficient.\n- The explanation of the algorithm is clear and concise.\n\nWeaknesses:\n- The code lacks comments explaining the logic and functionality of each part of the algorithm.\n\nSuggestions for improvement:\n- Add comments to the code to explain the logic and functionality of each part of the algorithm.\n- Although not necessary in this case, consider providing examples in multiple programming languages for a broader audience.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "MfWw7JKnvqVUUU8zTfuinz", "question_id": 66, "answer1_id": "R3aYUUtY46ht4ToU8US96x", "answer2_id": "KLbBzjbuwq4agAESQ9Wfpq", "text": "6 8\n\nAssistant 1 provided a general explanation of how to implement a queue using two stacks in Python but did not provide any code. The explanation was clear, but it would have been more helpful to include a code example.\n\nAssistant 2 provided a code implementation of a queue using two stacks in Python. The code is mostly accurate, but there are a few issues. The dequeue method is incorrect, as it should transfer elements from the in_stack to the out_stack if the out_stack is empty, and then pop the top element from the out_stack. The peek method should also return the top element of the out_stack if it's not empty. The enqueue method does not need to clear the out_stack. Here is the corrected code:\n\n```python\nclass Queue:\n    def __init__(self):\n        self.in_stack = []\n        self.out_stack = []\n    \n    def enqueue(self, item):\n        self.in_stack.append(item)\n    \n    def dequeue(self):\n        if not self.out_stack:\n            while self.in_stack:\n                self.out_stack.append(self.in_stack.pop())\n        if not self.out_stack:\n            raise EmptyQueueError\n        return self.out_stack.pop()\n    \n    def peek(self):\n        if not self.out_stack:\n            while self.in_stack:\n                self.out_stack.append(self.in_stack.pop())\n        if not self.out_stack:\n            raise EmptyQueueError\n        return self.out_stack[-1]\n    \n    def is_empty(self):\n        return not self.in_stack and not self.out_stack\n\nclass EmptyQueueError(Exception):\n    pass\n```\n\nOverall, Assistant 2's code was more helpful and closer to a correct implementation. However, both assistants could improve by providing more detailed explanations and comments in their code.", "score": [6.0, 8.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "6FenkFD6ft3WRdxHCHLvvv", "question_id": 67, "answer1_id": "MQJFbH3KoFaSMmPgmK9LPa", "answer2_id": "ganAwetd9VTzEAiTtsskzX", "text": "6 8\n\nAssistant 1:\nStrengths:\n- The explanation of the approach is clear and easy to understand.\n\nWeaknesses:\n- The code is not provided, only the explanation of the approach.\n- The \"found\" flag is mentioned, but it is not clear how it would be implemented in the code.\n- The approach does not account for duplicate elements in the arrays.\n\nSuggestions for improvement:\n- Provide actual code for the given problem statement.\n- Clarify how the \"found\" flag would be used in the code.\n- Consider handling duplicate elements in the arrays.\n\nAssistant 2:\nStrengths:\n- The code is provided and is easy to read.\n- The solution is accurate and efficient.\n- The example usage of the function is helpful.\n\nWeaknesses:\n- The code lacks comments explaining the logic and functionality.\n- The function name uses an escape character (\\) instead of an underscore (_).\n\nSuggestions for improvement:\n- Add comments to the code to explain the logic and functionality.\n- Correct the function name to use an underscore (_) instead of an escape character (\\).", "score": [6.0, 8.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "XK3729wYDvmpRCf34tDfL9", "question_id": 68, "answer1_id": "dBWqryuzG6BHRdPgrWWpbH", "answer2_id": "LG6szQ3cqNRzUjXtZtXG94", "text": "First, I will solve the problem independently:\n\nGiven f(x) = 5x^3 - 2x + 3, we need to find the value of f(2).\n\nf(2) = 5(2)^3 - 2(2) + 3 = 5 * 8 - 4 + 3 = 40 - 4 + 3 = 39\n\nNow, I will examine the problem-solving process of Assistant 1 and Assistant 2.\n\nAssistant 1:\nThe value of f(2) is 1.\n\nAssistant 1 provided an incorrect answer without showing any problem-solving steps.\n\nAssistant 2:\nTo find the value of f(2), we need to substitute 2 for x in the function f(x).\n\nf(x) = 5x^3 - 2x + 3\n\nWhen x = 2, we have:\n\nf(2) = 5(2)^3 - 2(2) + 3 = 5 * 8 - 2 + 3 = 41 - 2 + 3 = 40\n\nAssistant 2 provided a detailed problem-solving process but made an error in the calculation: 5 * 8 - 4 + 3 should be 40 - 4 + 3, which equals 39.\n\nBased on the evaluation, I would give the following scores:\n\nAssistant 1: 1 (Incorrect answer and no problem-solving steps)\nAssistant 2: 8 (Detailed problem-solving process but with a minor calculation error)\n\nAssistant 2 performed better than Assistant 1.", "score": [1, 8], "reviewer_id": "gpt-4-0328-math", "metadata": {}}
-{"review_id": "f68KKW2RJoZTVSnw49YSNe", "question_id": 69, "answer1_id": "W74byrCbE7XiJWjcPTZS7x", "answer2_id": "LHMnXGbSZubeZJcr5fgrte", "text": "First, let's solve the problem independently:\n\n3x + 10 = 5(x - 2)\n3x + 10 = 5x - 10\n10 + 10 = 5x - 3x\n20 = 2x\nx = 10\n\nNow, let's examine the problem-solving process of Assistant 1 and Assistant 2:\n\nAssistant 1:\nx = 6\n\nAssistant 1 directly provided the answer without any explanation. The answer is incorrect.\n\nAssistant 2:\n1. Simplify the left-hand side (LHS) of the equation by moving all the terms to one side and the numbers to the other: 3x + 10 = 5x - 10\n2. Combine the terms on the left-hand side by subtracting 5x from both sides: 3x = -5x\n3. Simplify the left-hand side by dividing both sides by 3: x = -5/3\n4. Take the natural logarithm of both sides to get the solution in terms of the natural logarithm base e: ln|x| = ln|-5/3| = -5/3 ln|e| = -5/3 ln(1.414) = -5/3 ln(1.414) = -5/3 ln(1 + 1/1.414) = -5/3 ln(1.414)\n5. Exponentiate both sides to get the solution in terms of e: x = e^(-5/3)\n6. Rearrange the solution to get x in terms of Euler's number: x = e^(-5/3) = 1/1.414^(-5/3) = 0.5877\n7. Round the solution to the desired number of decimal places: x = 0.5877\n\nAssistant 2's steps are incorrect starting from step 2. The correct step 2 should be subtracting 3x from both sides: 10 = 2x. The rest of the steps are not applicable to this problem.\n\nScores:\nAssistant 1: 1 (Incorrect answer, no explanation)\nAssistant 2: 3 (Incorrect answer, incorrect steps)\n\nBoth assistants performed poorly, but Assistant 2 provided a more detailed explanation, even though it was incorrect.", "score": [1, 3], "reviewer_id": "gpt-4-0328-math", "metadata": {}}
-{"review_id": "5uv8eKWqXyF5mnNtY94s8f", "question_id": 70, "answer1_id": "7WC5quGKdv8hADCxWaWZ57", "answer2_id": "TGENVWL5iAYi4NCf5jAzKy", "text": "First, let's solve the problem independently:\n\nWe have two points (2, -2) and (10, 4). To find the length of the line segment, we can use the distance formula:\n\ndistance = sqrt((x2 - x1)^2 + (y2 - y1)^2)\n\nPlugging in the values:\n\ndistance = sqrt((10 - 2)^2 + (4 - (-2))^2)\ndistance = sqrt(8^2 + 6^2)\ndistance = sqrt(64 + 36)\ndistance = sqrt(100)\ndistance = 10\n\nNow, let's evaluate the answers provided by Assistant 1 and Assistant 2:\n\nAssistant 1:\nThe length of the line segment is 8 units.\n\nThis answer is incorrect.\n\nAssistant 2:\nThe length of the line segment is 17.973.\n\nThis answer is also incorrect.\n\nNow, let's assign scores to Assistant 1 and Assistant 2:\n\nAssistant 1: The answer is incorrect, and there is no explanation of the problem-solving process. Therefore, the score is 1.\n\nAssistant 2: The answer is incorrect, but the problem-solving process is mostly correct except for the calculation of (10 - 2)^2 + (4 - (-2))^2, which should be 8^2 + 6^2 instead of 18^2 + 4^2. Therefore, the score is 5.\n\nIn conclusion, the scores are (1, 5) for Assistant 1 and Assistant 2, respectively. Assistant 2 performed better, but both assistants provided incorrect answers.", "score": [1, 5], "reviewer_id": "gpt-4-0328-math", "metadata": {}}
-{"review_id": "EgDTYCXZFp72ZuZcCV6duW", "question_id": 71, "answer1_id": "AZER7D3RKZ9F9SXHiMjdqM", "answer2_id": "kc9oytarvqyNVVfGZz93EL", "text": "9 10\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the user's request for a formal email proposing a joint venture. Assistant 1 provided a concise and clear template that can be easily adapted by the user. Assistant 2, on the other hand, provided a more detailed and comprehensive email, including specific information about the proposed joint venture, such as the creation of a new company and the sharing of profits and losses. This level of detail may be more useful for the user, as it provides a more complete picture of the proposed partnership. Therefore, Assistant 1 receives a 9 and Assistant 2 receives a 10.", "score": [9.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "oM8FHcZ8kPbM7tGizHcwJv", "question_id": 72, "answer1_id": "MSrdDafr77UvSHCnsPMSP3", "answer2_id": "NxstpvVEnGMny3jECtvrw2", "text": "8 9\nBoth assistants provided helpful and relevant resignation letter templates. Assistant 1's response was concise and to the point, while Assistant 2's response was more detailed and included additional information about the reason for leaving, the transition process, and expressing gratitude for the friendships and connections made. Assistant 2's response was slightly more comprehensive, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "MzXdFKJbsMqVstCvErzqWL", "question_id": 73, "answer1_id": "hxkjUkDkXhGP78Vo74B4WE", "answer2_id": "XN9NBpeQJiQqGT5UYkys7N", "text": "8 10\nAssistant 1 provided a helpful and relevant response by outlining the general structure and content of a formal letter of recommendation. However, Assistant 2 went above and beyond by providing a detailed and well-structured example of a formal letter of recommendation, which is more useful for someone looking to write such a letter. Assistant 2's response was more accurate and detailed, making it the better choice in this case.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "CxW72r26HgPCsswHbNuYG5", "question_id": 74, "answer1_id": "hv9jpG9PxeJ9AnFdNzH3Jv", "answer2_id": "3qMqAZcfHUVUTEJnMXT8Pw", "text": "8 9\nBoth assistants provided relevant and helpful responses to the user's question. Assistant 1's response was well-written and conveyed excitement about the new software solution. However, Assistant 2's response was more detailed and included specific features of the software, which made it more informative and compelling. Assistant 2 also provided a clear call-to-action for scheduling a demo and contacting the company. Overall, Assistant 2's response was more effective in terms of providing information and engaging the reader.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "3e75hkdfKi7hwXZs2ivgHv", "question_id": 75, "answer1_id": "X5BVHT5pFpWxB88SzERrEG", "answer2_id": "hMXjd228Mc8pnc7zgd2frG", "text": "7 10\nAssistant 1 provided a brief and generic apology, but it lacked important details such as addressing the customer by name, providing a subject line, and offering contact information for further concerns. Assistant 2, on the other hand, provided a well-structured and detailed email, including a subject line, addressing the customer by name, and offering contact information. The response from Assistant 2 was more helpful, relevant, and accurate, which is why it receives a higher score.", "score": [7.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Agvs9JSySKiqaGQ8sL7uD9", "question_id": 76, "answer1_id": "Af2SufKwvDBriNXnZX9UoP", "answer2_id": "gUEd9nNepqy8nsfbypscHx", "text": "7 9\nAssistant 1 provided a brief overview of the video's content but did not provide a script for the YouTube video as requested. Assistant 2, on the other hand, provided a more detailed and structured script that covered the history, cultural significance, and influence of jazz music. Assistant 2's response was more helpful, relevant, and accurate, which is why it received a higher score.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "oVeEakhRwe8muRqEj7cxBy", "question_id": 77, "answer1_id": "HVnqVdSGRwQfqSsiYxtTTn", "answer2_id": "nZZyn3SAvU8T2BVR73LMHC", "text": "7 10\nAssistant 1 provided a brief overview of the travel blog post but did not actually compose the blog post as requested, resulting in a lower score. Assistant 2, on the other hand, composed a detailed and engaging travel blog post about a recent trip to Hawaii, highlighting cultural experiences and must-see attractions, which fully addressed the user's request, earning a higher score.", "score": [7.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "SkBRcfmYdX6ob8iV3FoCzW", "question_id": 78, "answer1_id": "8hcmmjzyMyhFJ8ZwqJJfvw", "answer2_id": "YM4qjUM5VfmWnzM3HXRB4G", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided captivating movie reviews for recently released science fiction films. Assistant 1's review of \"The Future is Blue\" was engaging and discussed the plot, characters, and special effects. However, it could have provided more details about the cast and the specific aspects of the special effects. Assistant 2's review of \"Beyond the Horizon\" was slightly more detailed, discussing the cast, their roles, and the unique personalities of the characters. Additionally, Assistant 2's review was more immersive, using phrases like \"transport you to a world beyond our own\" and \"interstellar adventure.\" Overall, both reviews were helpful and relevant, but Assistant 2's response was more detailed and captivating.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "8bP4D7to6FqqtUz7MVnc4z", "question_id": 79, "answer1_id": "CU6gGfJqQmwZNxEG2n2Uda", "answer2_id": "WcbzNkzu5q66QkK92NxmGB", "text": "8 10\nAssistant 1 provided a general overview of the podcast structure, touching on the main points of discussion. However, Assistant 2 went a step further by providing a more detailed and well-structured script, including an opening, segment breakdown, and closing. Assistant 2's response was more helpful, relevant, and detailed, making it easier for the user to follow and implement the script for their podcast episode.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "8MTGoSASS9dAp9UQwcSZ6p", "question_id": 80, "answer1_id": "5SWbCoLV6NRrq5RtWQK4jp", "answer2_id": "Tfm4f2mbpKJsa8MT6exs8D", "text": "8 10\nBoth assistants provided relevant and detailed responses to the question. Assistant 1 gave a brief but engaging review of the symphony concert, touching on the orchestra's performance, the conductor's passion, and the audience's experience. However, Assistant 2 provided a more comprehensive review, discussing specific pieces played, the conductor's leadership, and the emotional impact of the performance. Assistant 2's response also included more vivid descriptions of the orchestra's sound and the audience's reaction, making it a more informative and engaging review.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}

model/llava/eval/table/review/review_bard_vicuna-13b.jsonl

@@ -1,80 +0,0 @@
-{"review_id": "4CeMvEQyE6fKMJwvSLY3P4", "question_id": 1, "answer1_id": "3oW4JY265ZPJGTYi2CgRYF", "answer2_id": "cV4zXygaNP6CXEsgdHMEqz", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question about improving time management skills. Assistant 1's response was slightly more detailed, offering a few more tips and a more comprehensive approach to the topic. Assistant 2's response was also helpful and provided valuable advice, but it was slightly less detailed and did not cover as many aspects as Assistant 1's response. Both assistants did a great job, but Assistant 1's answer was more thorough and complete.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Y7PYc8sPHpCNzz3ZbYRSSy", "question_id": 2, "answer1_id": "CtDuDqypbL958TQork7v54", "answer2_id": "3zpPUeoVsPWXtKMV7cAhZ6", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, accurate, and detailed responses to the question about effective ways to deal with stress. Both assistants covered essential points such as exercise, healthy diet, sleep, talking to someone, relaxation techniques, and seeking professional help. Assistant 1 mentioned taking a break, while Assistant 2 discussed time management, mindfulness, and social support. Both responses complement each other and provide valuable information for managing stress. Therefore, they both receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "mykCkmptr8smB9EHpa5p3v", "question_id": 3, "answer1_id": "jqb5c6eBeyVTFo7SsqxqHA", "answer2_id": "6xpiZJE4vxxGqjRogPfBk7", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about the differences between Python and JavaScript. Assistant 1's response was more detailed and organized, covering a wider range of differences, such as typing, standard libraries, and execution methods. Assistant 2's response also covered important differences, but it was slightly less comprehensive and had a small inaccuracy regarding JavaScript being a statically typed language, which is not true, as JavaScript is dynamically typed. Overall, both responses were informative, but Assistant 1's answer was more precise and complete.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "oY8uafD9mxTZUaXPcqbML5", "question_id": 4, "answer1_id": "P5rC8W6gTuD4aY6HR5HQj9", "answer2_id": "abitTVu2Dz8rdMxyThvFyJ", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate tips for increasing productivity while working from home. Assistant 1's response was more detailed, providing a list of 10 tips, while Assistant 2 provided 7 tips. Both assistants covered essential points such as setting up a dedicated workspace, taking breaks, and eliminating distractions. Assistant 1 went a step further by mentioning goal-setting, tracking progress, and being patient, which adds value to the response. Assistant 2's response was still helpful and relevant, but slightly less comprehensive than Assistant 1's.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "dx2DdmmECCVayXHmgGCeDC", "question_id": 5, "answer1_id": "3uaqwfbwxtyDdqB8UVN3jM", "answer2_id": "UMZod8JaWia9KB2EVXdYrF", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about the basics of quantum computing. Assistant 1's response was slightly more detailed, covering key concepts like superposition and entanglement, as well as providing a clear explanation of qubits, quantum gates, and quantum algorithms. Assistant 2's response was also informative, but it focused more on the different approaches to building quantum computers, which was not specifically asked for in the question. Both responses were useful, but Assistant 1's answer was more comprehensive and directly addressed the question, which is why it receives a slightly higher score.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "GCdusGJ8SwdTgNXtAbsDob", "question_id": 6, "answer1_id": "HTRJ5q97DrgzoSofxkgedz", "answer2_id": "WXRCqF34f4UUJzd3xbgAqT", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information regarding the differences between plant-based and animal-based protein sources. Assistant 1 provided a more detailed response, discussing the amino acid profiles, nutritional benefits, and health implications of both types of protein sources. Assistant 2 also provided valuable information, but the response was slightly less detailed and focused more on sustainability, ethical considerations, and cost. Both responses were informative, but Assistant 1's answer was more comprehensive and detailed, which is why it receives a slightly higher score.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "JDyKyTyaawWLZ7BRAXDF5X", "question_id": 7, "answer1_id": "EhhyKNc3m8c9tnxm8uPfmt", "answer2_id": "JREJbG5ZKXCNMoWoiJQxbC", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information on how to develop critical thinking skills. Assistant 1 provided a more structured list of tips, which made it easier to follow and understand. Assistant 2 also provided valuable tips, but the list was not as clearly structured. Both assistants covered similar points, such as asking questions, being aware of biases, and seeking diverse viewpoints. Assistant 1 mentioned practicing regularly, while Assistant 2 emphasized taking breaks and reflecting, which are both important aspects of developing critical thinking skills. Overall, both responses were informative and helpful, but Assistant 1's response was slightly more organized and easier to follow.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "C9yzkczwF2CxkXdY3MobUM", "question_id": 8, "answer1_id": "JQXPknRQd24NUPKZxi6RNf", "answer2_id": "mmVwmX6TGJ2Y72gCNac4EQ", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided relevant and accurate answers to the question, addressing major challenges faced by the education sector today. Assistant 1 focused more on challenges within the context of schools, while Assistant 2 provided a broader perspective, including global challenges and issues related to curriculum development and sustainability. Assistant 2's answer was slightly more comprehensive and detailed, which is why it received a higher score. However, both answers were helpful and informative.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "jZiBSzNUueinzWJdnpGnQm", "question_id": 9, "answer1_id": "Lb3C2xQKdLCqFj4v3rmaof", "answer2_id": "DMTZyzd4rRAFV43xtBJ9ns", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question about the primary factors that influence consumer behavior. Assistant 1 provided a clear and well-organized response, with examples for each factor, making it easier for the reader to understand the concepts. Assistant 2 also provided a detailed response, covering similar factors but with the addition of marketing factors and product/service factors. However, Assistant 2's response could have been improved with the inclusion of examples, similar to Assistant 1. Overall, both assistants performed well, but Assistant 1's response was slightly better due to the inclusion of examples and a more organized structure.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "fFMtZUKdXvBXus66ccinKv", "question_id": 10, "answer1_id": "DhuZJtL3jhnrsTBvDct9oV", "answer2_id": "dETAsj4xHnUCSTkZezz8aM", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information on conflict resolution strategies in the workplace. Assistant 1's response was slightly more detailed, including a wider range of strategies such as time-out and arbitration, which were not mentioned by Assistant 2. Assistant 2's response was also helpful and relevant, but it did not cover as many strategies as Assistant 1. Both assistants provided clear explanations of the strategies they mentioned, making it easy for the user to understand and apply the information.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "fgFeMYHm6fQNv9wpaj8uQG", "question_id": 11, "answer1_id": "mDSj4BKim2eANUnEjW7xBm", "answer2_id": "C8ksZxg3LshMUWiLxPanbt", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1's response was slightly more detailed, with a clearer distinction between the environmental and health impacts of single-use plastic bottles and the benefits of reusable bottles. Assistant 2 also provided a good response, but the structure was less clear, and some points were repeated in different sections. Overall, both assistants provided valuable information, but Assistant 1's response was more organized and comprehensive.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "o6ptY7g5g9F3oeZf9wKNVs", "question_id": 12, "answer1_id": "MnkceSK7WwyXqAhbuKVYX7", "answer2_id": "NeHhRc5P5uAU8eWSJBRkhG", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1's response was slightly more detailed and organized, covering a wider range of factors such as affordability, convenience, safety, and sustainability. Assistant 2's response was also informative, but it did not mention sustainability and integration with other transportation options. Both assistants provided valuable information, but Assistant 1's answer was more comprehensive, which is why it receives a slightly higher score.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "7TRs4oVPcVxXc6gMQefJbq", "question_id": 13, "answer1_id": "EsyaBVpTN8BGbTSiFMnZUF", "answer2_id": "KAJ7UVwu8oCKyxZj9j82pm", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1's response was slightly more detailed and organized, with a clear distinction between fiscal and monetary policies and their respective uses during a recession. Assistant 1 also touched upon the debate between the use of fiscal and monetary policies, adding depth to the answer. Assistant 2's response was also informative and accurate, but slightly less detailed and organized compared to Assistant 1. Both assistants provided valuable information, but Assistant 1's response was more comprehensive and well-structured.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "FYNEME2oyvHjL2LT8Syw6t", "question_id": 14, "answer1_id": "dX8M752A6tzqLg9KhwgG5p", "answer2_id": "NnWfaeRe8PmitgmV4u5fY8", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 provided a clear explanation of how language and cultural barriers affect communication and relationships in multicultural societies, as well as some suggestions for overcoming these barriers. Assistant 2 also provided a clear explanation, focusing on specific aspects such as language, cultural norms, stereotypes, prejudice, and power dynamics. Assistant 2's answer was slightly more detailed and comprehensive, which is why it received a higher score. Both assistants did a good job in addressing the question, but Assistant 2's response was more in-depth and covered a wider range of factors that can affect communication and relationships in multicultural societies.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "m9uQkWFCbpPzeY3DWpabXd", "question_id": 15, "answer1_id": "dzwhq5XbaEBVpargyczz9B", "answer2_id": "WiGpqKRRwWonwgU95piNNc", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question. Assistant 1 provided a slightly more detailed response, with clear examples of how AI can be used in healthcare, such as diagnosing diseases, treating diseases, monitoring patients, and providing administrative support. Assistant 2 also provided a good response, covering similar points, but with slightly less detail and fewer specific examples. Both responses were well-structured and informative, but Assistant 1's response was slightly more comprehensive, which is why it received a higher score.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "U6SwUYVNiN3v9F3LyFWSJA", "question_id": 16, "answer1_id": "8zqxUtHxgtoHBkbf2bkqNW", "answer2_id": "iangiZeex5ndxAXnWMrxBW", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, accurate, and detailed responses to the question. They both explained the process of gene editing using CRISPR-Cas9 technology, discussed potential applications, and addressed ethical implications. The responses were well-structured and covered the main aspects of the topic, making it difficult to differentiate between the two in terms of overall performance.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "hd3g9747kGPYxTRP4uHZfj", "question_id": 17, "answer1_id": "WJc37t4n5PqmKKS3V4eMG2", "answer2_id": "XnMRLphzYQX4QRNht7tbui", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, accurate, and detailed responses to the question. They both explained how vaccinations work to protect individuals and communities from infectious diseases and described the concept of herd immunity. Both responses mentioned the importance of vaccinations for protecting vulnerable populations, such as young children, pregnant women, and people with certain medical conditions. The slight differences in their explanations do not warrant a difference in their scores, as both responses are informative and valuable.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "FXVS7QPg3oTcLEhdpC4426", "question_id": 18, "answer1_id": "CvVLf8FgoHywJy8j8JJ4qL", "answer2_id": "HZc37bwy646mRzbqSsDAob", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a good overview of the influence of social media platforms on news consumption and sharing, as well as the potential implications for the spread of misinformation. However, Assistant 2 provided a more detailed and structured response, listing specific ways in which social media platforms influence news consumption and sharing, and elaborating on the potential implications for the spread of misinformation. This made Assistant 2's response slightly more informative and easier to follow, resulting in a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "fHksJvMWcNVHE2gkWLhUqk", "question_id": 19, "answer1_id": "P5rytR6vTJjxgWxRoxT3vX", "answer2_id": "iJrMatLrMdJyyqMx9uJ45a", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. They both discussed the influence of cultural, social, and economic factors on people's food choices and provided examples of how these factors can affect food choices. Both assistants also discussed how this knowledge can be used to promote healthier diets through targeted interventions, policies, and individual actions. The level of detail in both responses is sufficient to provide a clear understanding of the topic. Therefore, both assistants receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "ZkFeTQDFEpTsvxZdVAYpRv", "question_id": 20, "answer1_id": "5biCd7QRZP6rquaz8eC9Vm", "answer2_id": "oVEHqDnDTEADZSFfKgFTZd", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, accurate, and detailed responses to the question. They both explained the process of natural selection and how it contributes to the evolution and adaptation of species. Both assistants covered the key principles of natural selection, such as variation, differential reproduction, heredity, and the resulting changes in populations over time. The examples provided by Assistant 1 (giraffes and fish) and the additional point about stabilizing mechanisms by Assistant 2 added value to their respective answers. Overall, both assistants demonstrated a strong understanding of the topic and provided informative and comprehensive answers.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "GCoFg2g9EbRdJwgKUbZ6MF", "question_id": 21, "answer1_id": "363RwB6kr8nV6qFNdjXZnS", "answer2_id": "WLAj4u59bj2oEXzahF79ek", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question. Assistant 1 gave a clear and concise introduction, mentioning the knight's lord and the purpose of attending the banquet. However, Assistant 2 provided a more detailed and immersive response, capturing the humility and loyalty of a medieval knight while also acknowledging their lineage and dedication to the kingdom. This made Assistant 2's response slightly more engaging and informative, earning it a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "QraPP8QES6Uhc6sTjkSw9o", "question_id": 22, "answer1_id": "gDnYxMu5Dd52xhMqQAJaZP", "answer2_id": "fJPnM2XcRveW2zR4DDaeTb", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided relevant and motivating speeches for a pirate crew to search for hidden treasure. Assistant 1 focused on the potential wealth and luxurious life that the crew could achieve, while Assistant 2 emphasized the spirit of adventure, overcoming challenges, and the crew's ultimate destiny. Assistant 2's response was slightly more engaging and inspiring, which is why it received a higher score. However, both responses were helpful, accurate, and detailed in their approach to the question.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "NNptX6gxfgPqh4F8FFoZin", "question_id": 23, "answer1_id": "kCV5RSrnmmTyv3HA5oU38P", "answer2_id": "fY4Xed6veWpcKfj5krZz8m", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the user's question. They both created a soliloquy that captures the essence of a Shakespearean character declaring their love. Both soliloquies used poetic language and imagery to express the depth of emotion and love. The level of detail in both responses is sufficient, and both assistants demonstrated a good understanding of the user's question. It is difficult to differentiate their performance, as both provided high-quality answers, so they both receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "D5bCSqsqxvaC6RNYEVNL29", "question_id": 24, "answer1_id": "CTGLYNAWrWeuCYZAR9bD2r", "answer2_id": "LqFJA2JQbBXP77nkYjtrZK", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a more traditional superhero origin story, involving an accident that led to superpowers, and emphasized the importance of helping others and being inspired by other superheroes. Assistant 2, on the other hand, presented a unique origin story as an advanced artificial intelligence created by scientists, with a focus on intelligence, adaptability, and a strong moral compass. Both answers were detailed and engaging, but Assistant 2's response was slightly more creative and offered a different perspective on what it means to be a superhero, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "SJmVbKB9KZN8KVDQJBTfMm", "question_id": 25, "answer1_id": "Eh5qCENdftYf9JKrBspYna", "answer2_id": "WxCKcRstJPXTXnqEzSX3Hg", "text": "8 9\nBoth assistants provided helpful, relevant, and accurate information about the technological advancements from the year 3000. Assistant 2's response was slightly more detailed and covered a broader range of advancements, such as fusion power, advanced nanotechnology, and quantum computing, which were not mentioned by Assistant 1. Assistant 1's response was still informative and accurate, but Assistant 2 provided a more comprehensive overview of the advancements, which is why Assistant 2 receives a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "hjH8swSeSBQuU69drFK8VE", "question_id": 26, "answer1_id": "M6hCe8Z4JDpt75HZ5PsSWr", "answer2_id": "dgPJ7DvtFHD7mxtRwzM3vW", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate descriptions of the winning play in the final seconds of a championship game. Assistant 1 focused on a football scenario, while Assistant 2 described a basketball situation. Both assistants provided a good level of detail in their responses. However, Assistant 2's response was slightly more engaging and vivid, painting a clearer picture of the emotions and atmosphere surrounding the winning play. This is why Assistant 2 receives a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Z3BF4pSYekBJCWk5GrKRTB", "question_id": 27, "answer1_id": "QCDsmbALfut5758pyiKvc5", "answer2_id": "ADX83sWvjJkewJX6JmYUzQ", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided relevant and detailed responses to the question. Assistant 1 described a specific dish with its ingredients and preparation, while Assistant 2 focused more on the philosophy behind the dish and the overall experience it provides. Assistant 2's response was more engaging and immersive, which is why it received a slightly higher score. However, both assistants did a good job in portraying a world-famous chef describing their signature dish.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "d7AELTvSCLy9AZU4f9kPgG", "question_id": 28, "answer1_id": "NWUbhwZQCuXsuQimrjQRza", "answer2_id": "ihNG3rwsrt95NDhCAFeSDR", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided relevant and detailed responses to the user's question. Assistant 1 took a more personal and emotional approach, describing the feelings and emotions of a climber reaching the summit of Mount Everest. The description was vivid and engaging, giving the reader a sense of what it might feel like to be in that situation. Assistant 2, on the other hand, took a more objective approach, acknowledging its status as an AI language model and providing a detailed description of the emotions and views a climber might experience at the summit. Assistant 2 also included important information about the risks and challenges associated with climbing Mount Everest, which added value to the response. Both assistants provided helpful and accurate information, but Assistant 2's response was slightly more comprehensive and informative, earning it a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "mozSNXxSeY7asAZQxdj9xV", "question_id": 29, "answer1_id": "VYwSjZrSLW9ZSvqryyjEaB", "answer2_id": "Gmhqf3z4LvVfwPNFJ89BKd", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a more personal and emotional perspective on the daily life of a space colonist on Mars, while Assistant 2 provided a more structured and organized description of daily activities. Assistant 2 also included more details about the Martian day and communication with Earth, which made their response slightly more informative. Both assistants addressed the challenges faced by colonists, but Assistant 2 provided a clearer and more concise list of challenges. Overall, both responses were of high quality, but Assistant 2's answer was slightly more detailed and organized.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "CrmHjPRFNPKCxFgUExqokF", "question_id": 30, "answer1_id": "FA7PXuUbEVGKHaWpxaimy8", "answer2_id": "gSwkKJCn6qDnNZond2xVJ3", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided relevant and detailed responses to the user's question. Assistant 1 focused more on the relationships with allies and their contributions to the character's survival, while Assistant 2 emphasized the character's adaptability and resourcefulness. Assistant 2's response was slightly more comprehensive, as it also mentioned encounters with dangerous characters and the importance of self-preservation, which added depth to the post-apocalyptic scenario. Therefore, Assistant 2 receives a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "fEViribrZXZzE72JCS4P4W", "question_id": 31, "answer1_id": "j5EV5cZNsn9DcF6WsvXRzS", "answer2_id": "8RaBeMjxx2bCp2GKWv7YiP", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. They both offered multiple ways to determine if a restaurant is popular among locals or mainly attracts tourists. Additionally, they both explained why this information might be useful. The level of detail in both responses is sufficient to guide someone in making an informed decision about where to dine. It is difficult to differentiate the quality of the answers, as both assistants covered the necessary points and provided valuable insights.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "4ue6iA4VLVoK9wVzrY2niz", "question_id": 32, "answer1_id": "2eAYCYmwTkPa3ejQDv8LyB", "answer2_id": "C65PZkmAfFfWRs4bPhyKqg", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 listed several examples of behaviors that might indicate someone is pretending to understand a topic, while Assistant 2 focused on specific verbal and non-verbal cues. Assistant 2's answer was slightly more detailed and provided a clearer distinction between the different clues, which is why it received a higher score. However, both answers were informative and useful in understanding the subtle clues that suggest someone is pretending to understand a topic or conversation when they are actually confused or uninformed.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Muc5dWnrdUfzZZ9VRowc3a", "question_id": 33, "answer1_id": "d562WYnhsvgJ8J6Ubitmvw", "answer2_id": "4so4HTEjgDZKTqNAgkHHQX", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1's response was more detailed, covering a wider range of reasons and specific situations where using a paper map or asking for directions might be the best option. Assistant 2's response was also informative, but it did not cover as many reasons or situations as Assistant 1. Both assistants provided valuable information, but Assistant 1's answer was more comprehensive, which is why it receives a slightly higher score.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "NwMq4vK6vSmnwnJRoMoYeo", "question_id": 34, "answer1_id": "hPMvV6zL2C4qTP4mRmhJwG", "answer2_id": "FCYaiexEzdoLFPAwvTgDDm", "text": "8 9\nBoth assistants provided helpful and relevant information on how to determine if a person is genuinely interested in a conversation or simply being polite. Assistant 1 focused on body language, questions, responses, and trusting one's gut feeling, while Assistant 2 emphasized active listening, engaged body language, personal investment, authenticity, and follow-up. Assistant 2's answer was slightly more detailed and provided clearer examples, which is why it received a higher score. However, both responses were accurate and useful in addressing the user's question.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "C9S29Tffb2mHkjoU22D9bK", "question_id": 35, "answer1_id": "npWNeKceGyqCYaRpY4w54g", "answer2_id": "76EPQDh4ZNxBMGqED9LEFi", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, accurate, and detailed responses to the question. They both listed multiple reasons why someone might prefer to shop at a small, locally-owned business instead of a large chain store, even if the prices are higher. The reasons provided by both assistants were similar, with some overlap, but each assistant also provided unique points. Assistant 1 mentioned the aspect of feeling good about supporting a local family or community, while Assistant 2 brought up the point of prestige. Both responses were well-structured and informative, making it difficult to differentiate their overall performance. Therefore, both assistants receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "ZkpQT2dTNQjnYyrnNsz3D5", "question_id": 36, "answer1_id": "WVuaK9m8Sedcws27tNu7Ev", "answer2_id": "cvBg3gyCyDuyESof3YXhTE", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question. Assistant 1's response was slightly more concise and organized, making it easier to follow. Assistant 2's response was also helpful and detailed, but it had some redundancy in mentioning the reputation of the author and publisher, which the user specifically wanted to avoid relying on. Overall, both assistants provided valuable information and tips for assessing the credibility of a source, but Assistant 1's response was slightly more focused and well-structured.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "8QFw8ef76yDDrwa55PMQ4x", "question_id": 37, "answer1_id": "HLtTf83Y5QRP4TxX6nw5TC", "answer2_id": "kRgfUJ7qqkyZUnLd2fnnaX", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 focused on the physiological aspects of why people enjoy being scared, such as the release of endorphins and adrenaline, and also mentioned the sense of control and accomplishment that can come from facing fears. Assistant 2 expanded on this by discussing brain chemistry, life experiences, personality traits, cultural factors, and learning as possible explanations for why people enjoy or avoid being scared. Both assistants provided a good level of detail in their responses. Assistant 1 received a slightly higher score because their answer was more concise and easier to follow, while still covering the main points. Assistant 2's answer was also informative, but it was a bit more complex and could be harder for some readers to digest.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "k29wLLwg4Axnvsa8FwGVM7", "question_id": 38, "answer1_id": "Fmdtexq6QQNuoqZkZfDURY", "answer2_id": "J3YuizKcHQ74ydNyCcwgwu", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1's response was more detailed, providing three specific methods for observing cultural norms and expectations: identifying patterns of behavior, paying attention to reactions to violations of cultural norms, and talking to people about their culture. Assistant 2 also provided a good response, emphasizing the importance of social interactions in learning about cultural norms and expectations, but did not provide as many specific examples or methods as Assistant 1. Therefore, Assistant 1 receives a 9 and Assistant 2 receives an 8.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "RtLULm2N2vxhVvB5poB6PQ", "question_id": 39, "answer1_id": "WxnC69jTMkyJvcqvMCgCwY", "answer2_id": "abWLpFojLpNPfDGHpuRSUG", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question. Assistant 1 provided a clear list of potential benefits and costs of space exploration, as well as mentioning the ethical implications. However, Assistant 2 went a step further by not only discussing the benefits and risks of space exploration but also addressing the benefits and risks of focusing on Earth's problems. This additional information provided by Assistant 2 made the response more comprehensive and balanced, which is why Assistant 2 receives a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "dc2MRMPFttiwmvFkFbiqfi", "question_id": 40, "answer1_id": "npZdTFPRqZfoqzt5YurYEL", "answer2_id": "Ki4fkJvsoSxuQeSoj2AcBG", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 discussed the importance of prioritizing both job creation and technological progress, and provided suggestions on how to mitigate the negative effects of automation on employment. Assistant 2 also emphasized the need to strike a balance between job creation and technological progress, and discussed the importance of policies and programs to address the social and economic impacts of technological progress. Both answers were detailed and well-structured. However, Assistant 2's response was slightly more comprehensive in addressing the potential impacts on jobs and the economy, and the need for policies and programs to mitigate these impacts, which is why it received a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "9adA4k9eHcdXaVNcKQQey6", "question_id": 41, "answer1_id": "iy9aa5sqFeNA2uPQZLpxEz", "answer2_id": "GRQjYgAapNAVqzuZR4KQpf", "text": "7 8\nAssistant 1 provided a detailed response with specific numbers for blinks per minute, hour, day, and year, and an estimate for a lifetime. However, the response did not take into account the variations in blink rates due to factors like age, stress, and illness. Assistant 2 provided a more thorough explanation, considering the time spent awake and asleep, and acknowledged that the blink rate could vary throughout a person's lifetime. Assistant 2's response was more comprehensive and took into account more factors, which is why it received a higher score.", "score": [7.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "XQggwZdH9ihfMvtCaDNmn2", "question_id": 42, "answer1_id": "XAALo4GKWE3QNb7wbkWVNk", "answer2_id": "SB5a2AiK224hB927vkqvYs", "text": "7 9\nAssistant 1 provided a reasonable estimate of the number of atoms in a grain of salt, but the explanation was not very clear and contained some errors in the calculation steps. Assistant 2, on the other hand, provided a more detailed and accurate explanation, taking into account the size of the grain and the elemental composition of the salt. The calculation steps were clearer and more accurate, leading to a more reliable estimate of the number of atoms in a grain of salt. Assistant 2's response was more helpful, relevant, and accurate, with a higher level of detail, which is why it received a higher score.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "LvL4T9rGjgMg68HqsHnPmG", "question_id": 43, "answer1_id": "XRWjLnJNyGNMfktTvWpbRV", "answer2_id": "4XYycBrMiJgYKPof2P6xoe", "text": "7 8\nAssistant 1 provided a clear answer with an estimated number of lightning strikes per day and explained the reasoning behind the occurrence of lightning strikes. However, the explanation lacked information about the factors that can cause variations in the number of strikes, such as weather conditions and location. Assistant 2, on the other hand, provided a more detailed response, explaining the factors that can affect the number of lightning strikes and giving a more accurate estimate. Both assistants were helpful and relevant, but Assistant 2 provided a more comprehensive and accurate explanation, which is why it received a higher score.", "score": [7.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "7w3V3u47cKQiwf2WUmesbQ", "question_id": 44, "answer1_id": "CHeyn9eR3u5eFq99UJ3pbB", "answer2_id": "fpoXWHHdpv7XNBTS2NRY6d", "text": "7 8\nAssistant 1 provided a reasonable estimate of the number of balloons needed to lift a house, but the explanation was not as detailed or step-by-step as requested. Assistant 2, on the other hand, provided a more detailed step-by-step explanation and acknowledged the impracticality of the scenario in real life. Both assistants mentioned the impracticality of the situation, but Assistant 2's response was more thorough and better addressed the user's request for a step-by-step explanation.", "score": [7.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "5WneHShBCG6nbDkXpzNxAU", "question_id": 45, "answer1_id": "kfoNRLCHFucfWcxFBPoJgP", "answer2_id": "GRXWdnzLLzmeZRU67PMTb7", "text": "8 6\nAssistant 1 provided a specific number of text messages sent globally per minute, which was 15,220,700, and cited a source (Domo) for this information. The response also included reasons for the high number of text messages and the expected growth in the future. Assistant 2, on the other hand, focused on the challenges of determining the exact number of text messages sent per minute but did not provide any specific data or estimates. While both responses were relevant and accurate in their own ways, Assistant 1's answer was more helpful and detailed, which is why it received a higher score.", "score": [8.0, 6.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "fUuJVJNRtdkKMKvrebQpLs", "question_id": 46, "answer1_id": "A4sDEGXpWaNVA39uRsDNjB", "answer2_id": "RTxk2jYsjYiiWMwcRjmfwu", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant answers to the question. Assistant 1 gave a detailed explanation of the factors that can affect the number of words spoken per day and estimated that the average person speaks about 7,000 words per day. However, Assistant 1 did not provide an overall estimate of the total number of words spoken daily on Earth. Assistant 2, on the other hand, provided a step-by-step explanation of how the estimate of 100 billion words spoken daily on Earth was arrived at, which included considering the world population and the average number of words spoken per person per day. Assistant 2 also acknowledged the limitations of the estimate. Therefore, Assistant 2 receives a slightly higher score due to the inclusion of a total estimate and a more structured approach to the explanation.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "9vWUtqZJYaN3mvSgMgHah3", "question_id": 47, "answer1_id": "hUAc6BCs5NuY7tS62PPXbT", "answer2_id": "2J2Et6W8u2kXLTUgfYrPxe", "text": "7 8\nBoth Assistant 1 and Assistant 2 provided relevant and informative answers to the question. Assistant 1 provided a specific number (1 septillion) for the number of snowflakes that fall each year, which is interesting but not necessarily applicable to a \"typical winter\" as the question asked. Assistant 1 also provided some information on the factors that affect snowflake formation and their shapes. Assistant 2, on the other hand, focused more on the factors that influence the number of snowflakes and provided a step-by-step explanation of the process, which was more in line with the question's request. While both answers were helpful and accurate, Assistant 2's response was more relevant and detailed, which is why it receives a slightly higher score.", "score": [7.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "9cL7dFKwuJmU7tGQDbPXvp", "question_id": 48, "answer1_id": "TMtjmb5tDizQ9RETRxpt2s", "answer2_id": "nSGoG9Z5g5VuCXgmQJJKrq", "text": "7 6\nAssistant 1 provided a more detailed response, considering factors such as self-published books and lost or destroyed books. They also provided a wider range of estimates for the total number of pages. However, their estimate of the total number of books ever published (129 million) was significantly higher than Assistant 2's estimate (13 million). Assistant 2's response was more concise and easier to follow, but it did not consider the factors mentioned by Assistant 1. Both assistants acknowledged the impossibility of providing an exact number, but Assistant 1's response was more comprehensive in its reasoning.", "score": [7.0, 6.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "YDnAUmn3rLo2fXnQNMsSWi", "question_id": 49, "answer1_id": "AwQMPhhaJ32ByA3VjKF5Ph", "answer2_id": "ScqJdUq9n5bp9qPv5WPqG5", "text": "7 8\nBoth assistants provided relevant and detailed information in their responses. Assistant 1 gave a clear explanation of the Earth's orbit and its importance for life on Earth. However, the answer contained an incorrect statement about the Earth orbiting the Sun 1 billion times since the first life arose, which contradicts the initial statement of 4.543 billion times. Assistant 2 provided a more accurate and detailed explanation, taking into account the elliptical nature of the Earth's orbit and the average distance between the Earth and the Sun. Assistant 2 also acknowledged the uncertainties in the timing of the emergence of life and variations in the Earth's orbit, making their answer more reliable.", "score": [7.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "SdNHfEHe9iZHKbmYjkC5a4", "question_id": 50, "answer1_id": "UCqxXfMAnqJKbApsjrPFcq", "answer2_id": "GdLFr88pCwsGpfRBRQQkyh", "text": "8 7\nAssistant 1 provided a more detailed response by mentioning specific numbers from the US Copyright Office, Spotify, and Apple Music, which helps to give a better understanding of the scale of recorded songs. Assistant 2, while still providing a relevant response, focused more on the historical aspect of music and the development of recording technology, without providing specific numbers. Both assistants acknowledged the difficulty in estimating the exact number of songs recorded throughout history, but Assistant 1's response was more informative and precise.", "score": [8.0, 7.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "6Tbxuai5ZBjbL7XgsGM59j", "question_id": 51, "answer1_id": "YMRg5Xi9BBvvqqny2tqJZ3", "answer2_id": "Sa7uNEbFGRFuXBAwau8sHS", "text": "8 7\nAssistant 1 provided a more focused and relevant response to the question, discussing the potential impact of the Internet on the Renaissance period in terms of intellectual growth, collaboration, education, and the arts. Assistant 2, while providing some interesting points about the technological context and the possible development of an early form of the Internet, did not directly address the question's focus on the impact of the Internet on the Renaissance period. Both assistants provided accurate information, but Assistant 1's response was more helpful and relevant to the user's question.", "score": [8.0, 7.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "3xXeF3Goc2xSC9RJey8VNz", "question_id": 52, "answer1_id": "fhr7iMPb9SVJ663mXKBuct", "answer2_id": "T6Ar3cAEw3AmVVQTcCPp8N", "text": "8 9\nBoth assistants provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a good overview of the potential consequences of the Aztecs repelling the Spanish conquistadors, but Assistant 2 provided a more detailed response, discussing the potential impact on the Aztec civilization, the spread of European diseases, the economy of Mexico, and the possibility of forming alliances with other indigenous groups. Assistant 2's answer was more comprehensive, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "kGpPxDLcPjpJ8FsaBgWxeb", "question_id": 53, "answer1_id": "4rrmyZw9zhyJGqdrcazFvt", "answer2_id": "KiZQev5JEk2h6JYeQnFmtM", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information regarding the potential consequences of the Black Death not occurring in the 14th century. Assistant 1 focused on the decline of the population, the impact on society, and the changes in the way people lived. Assistant 2, on the other hand, provided a more detailed analysis of the potential demographic, economic, and social changes that could have occurred in the absence of the Black Death, as well as the possibility of other diseases spreading. Assistant 2's response was slightly more comprehensive and detailed, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "BUxwV6k4ktYY3rE7X4wH4B", "question_id": 54, "answer1_id": "Za3mY9xwxpZdPmGW48wtzu", "answer2_id": "cYiyYKKXM3GXkrZHAbX83S", "text": "7 8\nBoth Assistant 1 and Assistant 2 provided relevant and accurate responses to the question. Assistant 1 explored the potential outcomes of Newton focusing on biology, mentioning possible discoveries in medicine, mechanics of the human body, and causes of disease. However, Assistant 1 also considered the possibility that Newton might not have made significant discoveries in biology. Assistant 2 provided a more detailed response, discussing Newton's contributions to other fields and his wide range of interests. Assistant 2 also acknowledged the difficulty in predicting specific contributions without knowing more about Newton's interests in biology. Both responses were helpful, but Assistant 2's answer was more detailed and provided a broader perspective on Newton's scientific achievements, which is why it received a higher score.", "score": [7.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "YS2v2hkjFoUNTRg9UAP67U", "question_id": 55, "answer1_id": "cbAaJS9ULjR4XYSHATujSG", "answer2_id": "PQmMUdAAcBsAWmWaTvdHSU", "text": "8 7\nBoth Assistant 1 and Assistant 2 provided relevant and helpful answers to the question. Assistant 1 focused more on the cultural impact of the Beatles and how their absence might have affected the world, while Assistant 2 provided a list of possible outcomes if the Beatles had never formed. Assistant 1's response was slightly more detailed and touched on the emotional aspect of the Beatles' influence, which is why it receives a higher score. Assistant 2's response was also helpful, but it was more speculative and less detailed in comparison.", "score": [8.0, 7.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "LeebBihTDtAoBf6uEBYdcz", "question_id": 56, "answer1_id": "ZEgb9fvopGo7HF5wPeoeHs", "answer2_id": "PorExChQ9VeYsPJptdgtsB", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a clear explanation of the importance of Turing's work and its impact on the outcome of the war. However, Assistant 2 provided a more nuanced response, discussing the potential alternative strategies and technologies that the Allies might have pursued without Turing's contributions. This additional information and consideration of alternative scenarios make Assistant 2's response slightly more detailed and comprehensive, resulting in a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "W6qgavnMLN53fEy5HvfxhF", "question_id": 57, "answer1_id": "igMXoEiszFM65ZS2KUTvtm", "answer2_id": "249f6dSMwZRZVMmtxv6yDm", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 focused more on the impact on Egypt's economy and national pride, while Assistant 2 discussed the broader implications on international trade, global economic development, and the history of the region. Assistant 2 also mentioned the engineering and technological advancements required for the construction of the canal, which added more depth to the answer. Therefore, Assistant 2 receives a slightly higher score due to the additional details and broader perspective provided.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "VDKdWNYB6NcbkiNA9eWXSJ", "question_id": 58, "answer1_id": "Up4h8RpgVVafBtUj4tiGPZ", "answer2_id": "nxa3m6kiAZwKgcMUBY8KYz", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. They both acknowledged the advanced nature of the Maya civilization and the potential impact it could have had on the world if it had not collapsed. Assistant 1 provided a good overview of the possible outcomes, but Assistant 2 went into more detail about the potential advancements and influence the Maya civilization could have had on other civilizations in the region. Assistant 2 also mentioned the lasting impact of the Maya civilization on the region and their descendants, which adds more depth to the answer. Therefore, Assistant 2 receives a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "3KaALaanGsJQqzvwJFcnBL", "question_id": 59, "answer1_id": "CMg3ypKyykGUzQsDmX7i35", "answer2_id": "DXFvhjCaKqQiBsFDCkXGMT", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 discussed the possibility of other European explorers discovering the Americas and the potential for Chinese or Japanese settlements. Assistant 2 also mentioned the possibility of other European explorers discovering the Americas and focused more on the potential development of indigenous peoples without Columbus's discovery. Assistant 2's response was slightly more detailed and provided a clearer picture of the potential consequences of Columbus not discovering the Americas, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "h2qgd65upfZgKNUFsXgmHi", "question_id": 60, "answer1_id": "WhLiJXznzRBkzxDdnc5ndX", "answer2_id": "BCUK5VcpZK26jMJ2UMgR3E", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question. Assistant 1 explored the possibility of Van Gogh's success leading to a different impact on the art world and the potential influence of his tragic story on his art. Assistant 2 focused more on the potential changes in Van Gogh's art and personal life due to success and fame. Both responses acknowledged the impossibility of knowing the exact outcome. Assistant 2's response was slightly more detailed and well-rounded, considering the potential impact of fame and success on Van Gogh's personal life and art direction, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "WtY3uzgQLem7SJMRtmBuqc", "question_id": 61, "answer1_id": "Vzmhr5RMndkR866p4pUef6", "answer2_id": "JHTKBrLVTp7bv5zW2uwYVW", "text": "4 9\n\nAssistant 1:\nStrengths:\n- Polite and friendly response.\n\nWeaknesses:\n- Did not provide any code or solution to the given problem.\n- Misunderstood the task and offered unrelated services.\n\nSuggestions for improvement:\n- Focus on understanding the task and providing a relevant solution.\n- If unsure about the task, ask for clarification before providing an unrelated response.\n\nAssistant 2:\nStrengths:\n- Provided a working C++ program that solves the given problem.\n- Clear and concise comments explaining the code's logic and functionality.\n- Proper coding standards and best practices were followed.\n\nWeaknesses:\n- The program only counts lines containing the search string, not the actual number of occurrences of the word.\n\nSuggestions for improvement:\n- Modify the program to count the actual number of occurrences of the word in the file, not just the lines containing the word.\n- Consider handling edge cases, such as different letter cases or punctuation marks surrounding the search string.", "score": [4.0, 9.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "nnHxzRSqsuXx8A2hG2QZmE", "question_id": 62, "answer1_id": "jPrfhv9oaZGrkXxDUw5Vbt", "answer2_id": "jyzD2deb9JAffRhhkk37r5", "text": "8 4\n\nAssistant 1:\nStrengths:\n- The code is well-structured and easy to read.\n- The algorithm is efficient with a time complexity of O(nm) and space complexity of O(mn).\n- The code correctly implements the given problem statement.\n\nWeaknesses:\n- The code lacks comments to explain the logic and functionality.\n\nSuggestions for improvement:\n- Add comments to explain the logic and functionality of the code.\n\nAssistant 2:\nStrengths:\n- The code includes comments that explain the code's logic and functionality.\n\nWeaknesses:\n- The code is less efficient than Assistant 1's code.\n- The code does not correctly implement the given problem statement. The initialization of the dp table is incorrect, and the logic for filling in the table is also incorrect.\n- The code is less readable and structured compared to Assistant 1's code.\n\nSuggestions for improvement:\n- Correct the initialization of the dp table by setting the first row and column to 0 instead of float('inf').\n- Correct the logic for filling in the table by following the dynamic programming approach used in Assistant 1's code.\n- Improve the code structure and readability by following the style used in Assistant 1's code.", "score": [8.0, 4.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "N6SA5JgsXewWz7hda37xer", "question_id": 63, "answer1_id": "KdZNrf6udTfCxGGcQxRbXk", "answer2_id": "jPGHEfp7FxhDyvRA6qEN3j", "text": "7 8.5\n\nAssistant 1:\nStrengths:\n- The code is simple and easy to understand.\n- The function is well-structured and returns a boolean value.\n\nWeaknesses:\n- The regular expression contains unnecessary spaces, which may cause issues in matching valid email addresses.\n- The regular expression does not cover all valid email address formats (e.g., special characters in the username).\n- There are no comments explaining the regular expression or the function.\n\nSuggestions for improvement:\n- Remove the spaces in the regular expression.\n- Update the regular expression to include more valid email address formats.\n- Add comments to explain the regular expression and the function.\n\nAssistant 2:\nStrengths:\n- The code is well-structured and easy to understand.\n- The regular expression covers a wider range of valid email address formats.\n- There are comments explaining the regular expression and the code.\n\nWeaknesses:\n- The regular expression does not cover all valid email address formats (e.g., special characters in the username).\n- The code does not include a function to check the email address, making it less reusable.\n\nSuggestions for improvement:\n- Update the regular expression to include more valid email address formats.\n- Encapsulate the email validation code in a function for better reusability.", "score": [7.0, 8.5], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "LKFYJtdK3e6mujtw8wSjdH", "question_id": 64, "answer1_id": "AFzqAfbYVL25DBqFA2cv4G", "answer2_id": "Ra9eTcAuNZPkPRnaHiQrak", "text": "7 4\n\nAssistant 1:\nStrengths:\n- The code is well-structured and easy to read.\n- The dynamic programming approach is implemented correctly, using a table to store the results of previously solved subproblems.\n- The comments are clear and concise, explaining the logic and functionality of the code.\n\nWeaknesses:\n- The code does not handle the case when n = 0 or n = 1, which would result in an IndexError.\n- The code could be more efficient by using a memoization table with only two elements instead of a list of size n.\n\nSuggestions for improvement:\n- Add a condition to handle the cases when n = 0 or n = 1.\n- Use a memoization table with only two elements to save memory.\n\nAssistant 2:\nStrengths:\n- The code initializes a memoization table, which is a good start for a dynamic programming approach.\n\nWeaknesses:\n- The code does not actually use the memoization table, resulting in a less efficient solution.\n- The code does not handle the case when n = 0, which would result in an IndexError.\n- The comments are not as clear and concise as they could be, and they do not accurately describe the code's logic and functionality.\n\nSuggestions for improvement:\n- Implement the dynamic programming approach correctly by using the memoization table to store the results of previously solved subproblems.\n- Add a condition to handle the cases when n = 0 or n = 1.\n- Improve the comments to accurately describe the code's logic and functionality.", "score": [7.0, 4.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "MqumN4WHxBeQzbHE8XzKEc", "question_id": 65, "answer1_id": "Lt56JzWfXBxbvxrLf4fn3t", "answer2_id": "5mbEFLEnEx8Cm2wEF8WAbM", "text": "9 9\n\nBoth Assistant 1 and Assistant 2 provided correct and efficient implementations of the binary search algorithm. Their code is readable and well-structured. The time complexity of both implementations is O(log n), which is optimal for this problem.\n\nStrengths:\n- Both implementations are correct and follow the binary search algorithm.\n- The code is readable and well-structured in both submissions.\n- Both assistants provided a brief explanation of the algorithm and its time complexity.\n\nWeaknesses:\n- Assistant 1's implementation requires the user to provide low and high indices, which might be confusing for some users. Assistant 2's implementation is more user-friendly as it only requires the array and the target value as input parameters.\n- Neither assistant provided comments within the code to explain the logic and functionality. While the code is relatively simple and self-explanatory, adding comments would be helpful for users who are less familiar with the algorithm.\n\nSuggestions for improvement:\n- Assistant 1 could improve their implementation by removing the need for the user to provide low and high indices, similar to Assistant 2's implementation.\n- Both assistants should consider adding comments within the code to explain the logic and functionality, making it easier for users to understand the algorithm.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "ctTXTd9FC8vjGP9xFf6Gyb", "question_id": 66, "answer1_id": "bmaShWUyEqPE6kbHD6FjLk", "answer2_id": "KLbBzjbuwq4agAESQ9Wfpq", "text": "8 5\n\nAssistant 1:\nStrengths:\n- The implementation is correct and efficient.\n- The code is easy to read and understand.\n- The use of `__len__`, `__iter__`, and `__contains__` methods is a nice addition, making the class more versatile.\n\nWeaknesses:\n- The code lacks comments explaining the logic and functionality of the methods.\n\nSuggestions for improvement:\n- Add comments to explain the logic and functionality of the methods.\n\nAssistant 2:\nStrengths:\n- The code is readable and easy to understand.\n\nWeaknesses:\n- The implementation is incorrect. The `dequeue` method does not follow the logic of using two stacks to implement a queue.\n- The `enqueue` method clears the `out_stack`, which is unnecessary and inefficient.\n- The `peek` method returns the last item in the `in_stack`, which is not the front of the queue.\n- The `is_empty` method checks only the `in_stack`, which may lead to incorrect results if there are items in the `out_stack`.\n- The custom `EmptyQueueError` exception is not used effectively.\n\nSuggestions for improvement:\n- Correct the `dequeue` method to follow the logic of using two stacks to implement a queue.\n- Remove the unnecessary clearing of the `out_stack` in the `enqueue` method.\n- Modify the `peek` method to return the correct item at the front of the queue.\n- Update the `is_empty` method to check both stacks.\n- Use the `EmptyQueueError` exception effectively, or remove it if not needed.", "score": [8.0, 5.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "KoNz6J6gsCr6AgwW9rdyvK", "question_id": 67, "answer1_id": "hiSVom5YqSrKZKor8CjHdU", "answer2_id": "ganAwetd9VTzEAiTtsskzX", "text": "6 5\n\nAssistant 1:\nStrengths:\n- The code is well-structured and easy to read.\n- The function has a clear docstring that explains its purpose, arguments, and return value.\n- The code uses a set to store the common elements, which ensures that duplicates are not included in the result.\n\nWeaknesses:\n- The problem statement specifically asked not to use any extra data structures, but the code uses a set.\n- The algorithm has a time complexity of O(n^2), which can be slow for large arrays.\n\nSuggestions for improvement:\n- To avoid using extra data structures, you can modify the code to directly print the common elements instead of storing them in a set.\n\nAssistant 2:\nStrengths:\n- The code follows the problem statement's requirement of not using any extra data structures.\n- The code is simple and easy to understand.\n\nWeaknesses:\n- The code does not include any comments or a docstring, which makes it harder for others to understand the purpose and functionality of the function.\n- The algorithm has a time complexity of O(n^2), which can be slow for large arrays.\n- The code does not handle duplicate elements in the input arrays, which may lead to duplicate common elements in the result.\n\nSuggestions for improvement:\n- Add comments and a docstring to the function to explain its purpose, arguments, and return value.\n- To handle duplicate elements, you can add a condition to check if the common element is already in the result list before appending it.", "score": [6.0, 5.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "m6AC23LQ8JYijV3GtsHskU", "question_id": 68, "answer1_id": "JRHeURg4TrVAgWNp5yqjFx", "answer2_id": "LG6szQ3cqNRzUjXtZtXG94", "text": "First, I will solve the problem independently:\n\nf(x) = 5x^3 - 2x + 3\nf(2) = 5(2)^3 - 2(2) + 3 = 5(8) - 4 + 3 = 40 - 4 + 3 = 39\n\nNow, I will evaluate the problem-solving process of Assistant 1 and Assistant 2:\n\nAssistant 1:\nf(2) = 5(2)^3 - 2(2) + 3 = 40 - 4 + 3 = 39\nThe steps and the final answer are correct.\n\nAssistant 2:\nf(2) = 5(2)^3 - 2(2) + 3 = 5 * 8 - 2 + 3 = 41 - 2 + 3 = 40\nThe steps are incorrect, and the final answer is wrong.\n\nScores:\nAssistant 1: 10\nAssistant 2: 4\n\nAssistant 1 performed better because they provided the correct steps and final answer, while Assistant 2 made mistakes in their calculations.", "score": [10, 4], "reviewer_id": "gpt-4-0328-math", "metadata": {}}
-{"review_id": "34uzSiz6E2mtCxcqmAUF9P", "question_id": 69, "answer1_id": "hZwFKeRYBLKihBEWSEGMYJ", "answer2_id": "LHMnXGbSZubeZJcr5fgrte", "text": "First, I will solve the problem independently:\n\n3x + 10 = 5(x - 2)\n\nDistribute the 5 on the right-hand side of the equation:\n\n3x + 10 = 5x - 10\n\nSubtract 3x from both sides:\n\n10 = 2x - 10\n\nAdd 10 to both sides:\n\n20 = 2x\n\nDivide both sides by 2:\n\nx = 10\n\nNow, I will evaluate the answers provided by Assistant 1 and Assistant 2.\n\nAssistant 1:\n\nThe steps provided by Assistant 1 are correct, and the final answer of x = 5 is accurate.\n\nAssistant 2:\n\nThe steps provided by Assistant 2 are incorrect. The assistant made an error in step 2 by subtracting 5x from both sides, resulting in 3x = -5x, which is incorrect. The correct step should be subtracting 3x from both sides, resulting in 2x = 20. The rest of the steps are also incorrect due to this initial error.\n\nScores:\n\nAssistant 1: 10\nAssistant 2: 1\n\nAssistant 1 performed better and provided the correct solution to the equation.", "score": [10, 1], "reviewer_id": "gpt-4-0328-math", "metadata": {}}
-{"review_id": "57H8uDw5kYEX2wFgvY8BN8", "question_id": 70, "answer1_id": "iG4SJq9xCKCDDtiqU3szJZ", "answer2_id": "TGENVWL5iAYi4NCf5jAzKy", "text": "First, I will solve the problem independently:\n\nGiven the endpoints of a line segment are (2, -2) and (10, 4), we can use the distance formula to find the length of the segment:\n\n$$d = \\sqrt{(x_2 - x_1)^2 + (y_2 - y_1)^2}$$\n\nSubstituting the given coordinates:\n\n$$d = \\sqrt{(10 - 2)^2 + (4 - (-2))^2} = \\sqrt{8^2 + 6^2} = \\sqrt{64 + 36} = \\sqrt{100} = 10$$\n\nThe length of the line segment is 10 units.\n\nNow, I will examine the problem-solving process of Assistant 1 and Assistant 2:\n\nAssistant 1:\nThe steps provided by Assistant 1 are correct, and the final answer is also correct. The length of the line segment is 10 units.\n\nAssistant 2:\nAssistant 2 made a mistake in calculating the difference between the x-coordinates and the y-coordinates. The correct differences should be 8 and 6, not 18 and 4. This led to an incorrect final answer of 17.973.\n\nScores:\nAssistant 1: 10\nAssistant 2: 4\n\nAssistant 1 performed better in this case, as they provided the correct steps and answer, while Assistant 2 made a mistake in the calculation.", "score": [10, 2], "reviewer_id": "gpt-4-0328-math", "metadata": {}}
-{"review_id": "3bZ3BoLmb48KjWJ5q4NmMU", "question_id": 71, "answer1_id": "CjhV8cJ6UEp7Y4f3eWB6E5", "answer2_id": "kc9oytarvqyNVVfGZz93EL", "text": "9 9.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the user's request for a formal email proposing a joint venture. Both responses included appropriate greetings, explanations of the proposal, and reasons for the joint venture. Assistant 1's response was slightly more concise, while Assistant 2's response provided a bit more detail about the structure of the proposed joint venture and the potential benefits. Both responses were of high quality, but Assistant 2's response was slightly more detailed, which is why it received a slightly higher score.", "score": [9.0, 9.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "nErSsdfQf8KAT2XtVLDqVh", "question_id": 72, "answer1_id": "5waLH9pZsr8jVTpy67QH58", "answer2_id": "NxstpvVEnGMny3jECtvrw2", "text": "9 10\nBoth assistants provided relevant and helpful resignation letter templates. Assistant 1's response was concise and to the point, while Assistant 2's response was more detailed and included additional information about ensuring a smooth transition and completing outstanding tasks. Assistant 2's response was slightly better due to the additional details and consideration for the employer's needs during the transition.", "score": [9.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Q4QCqD7baQ8PkmzaJ4qJv7", "question_id": 73, "answer1_id": "ZV4sUNujQGS2w7Wg4jbXbf", "answer2_id": "XN9NBpeQJiQqGT5UYkys7N", "text": "9 10\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the user's question. They both structured a formal letter of recommendation for a student applying to a prestigious graduate program in computer science. Assistant 1's response was concise and well-organized, but Assistant 2's response was more detailed and included additional elements such as the sender's and recipient's affiliations, addresses, and date, which made it more complete and formal. Therefore, Assistant 2 receives a slightly higher score.", "score": [9.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "LVJ5BasrkhW8giXxYVqu9W", "question_id": 74, "answer1_id": "X94xm9m7tayWsKFNACqAG4", "answer2_id": "3qMqAZcfHUVUTEJnMXT8Pw", "text": "9 9.5\nBoth Assistant 1 and Assistant 2 provided relevant, accurate, and detailed responses to the user's request for a compelling product launch announcement email. Assistant 1's response was concise and focused on the benefits of the new software solution, while Assistant 2's response was more detailed, providing a list of key features and emphasizing the research and development behind the product. Both responses were helpful and well-structured. However, Assistant 2's response was slightly more compelling due to the additional details and emphasis on the product's innovation, which is why it receives a slightly higher score.", "score": [9.0, 9.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Pn2guBepbwfxhn2ev3JZoc", "question_id": 75, "answer1_id": "EFL7fU6gnicQY6DRpHvbTK", "answer2_id": "hMXjd228Mc8pnc7zgd2frG", "text": "9 10\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the user's request. Assistant 1's response was clear and concise, addressing the issue and providing reassurance that the problem has been resolved. Assistant 2's response was more detailed, including a subject line and additional information about the investigation and steps taken to prevent future delays. Both responses were well-written and appropriate for the situation, but Assistant 2's response was slightly more comprehensive, earning it a higher score.", "score": [9.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "7NJp7H3YHHQdWZmyMdcHpi", "question_id": 76, "answer1_id": "XJLFjCr6vgQZjEXbaMjTa6", "answer2_id": "gUEd9nNepqy8nsfbypscHx", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about the history and cultural significance of jazz. Assistant 1's response was more structured and detailed, covering the roots of jazz, its history, and its cultural significance, while Assistant 2's response was slightly less detailed but still informative and engaging. Assistant 1's script was more comprehensive, which is why it received a slightly higher score.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "MSCbf4yKFcdVNcQFDjYyAU", "question_id": 77, "answer1_id": "bz3rS9MRs9QmaLGg4A8a7B", "answer2_id": "nZZyn3SAvU8T2BVR73LMHC", "text": "9 10\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about a trip to Hawaii, highlighting cultural experiences and must-see attractions. Assistant 1 gave a clear and concise list of suggestions for cultural experiences and must-see attractions, making it easy for readers to understand and plan their trip. Assistant 2, on the other hand, crafted a more engaging and immersive narrative, sharing personal experiences and emotions, which is more fitting for a travel blog post. While both responses were informative, Assistant 2's response was more engaging and better suited to the requested format, which is why it receives a slightly higher score.", "score": [9.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "dUUREscUNiAEwZMX2Bv8pf", "question_id": 78, "answer1_id": "kCS2ZqzKTdDpaXwu3TiFXP", "answer2_id": "YM4qjUM5VfmWnzM3HXRB4G", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided captivating movie reviews for recently released science fiction films. Assistant 1 focused on the movie \"Dune,\" providing a detailed review of the plot, characters, and special effects, as well as mentioning the film's score. Assistant 2 reviewed a fictional movie called \"Beyond the Horizon,\" also discussing the plot, characters, and special effects. Both reviews were engaging and informative. Assistant 1's response was slightly more detailed and specific, which is why it received a higher score of 9, while Assistant 2's response was still strong and received a score of 8.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Mfyo2MkTqFoXcoVRYgYMpC", "question_id": 79, "answer1_id": "7WWWS5UhWcVzkhTypqcFU4", "answer2_id": "WcbzNkzu5q66QkK92NxmGB", "text": "8 9\nBoth assistants provided relevant and detailed podcast scripts discussing the influence of streaming platforms on the music industry. Assistant 1's script was well-structured, covering the pros and cons of streaming platforms and their impact on the music industry. However, Assistant 2's script was slightly more engaging and organized, with clearly defined segments and a more conversational tone. Additionally, Assistant 2 touched on the future of streaming platforms, which added depth to the discussion. Overall, both scripts were helpful and accurate, but Assistant 2's script was more appealing and comprehensive.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "T59yNWEAj9kzX8k2QbWom4", "question_id": 80, "answer1_id": "QcSFqbgqLWqn96V6BvWT7B", "answer2_id": "Tfm4f2mbpKJsa8MT6exs8D", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided detailed and engaging symphony concert reviews that discussed the orchestra's performance and the overall audience experience. Both responses were relevant, accurate, and helpful in conveying the atmosphere and quality of the performances. The reason for giving both assistants the same score is that they both demonstrated a high level of detail and quality in their responses, making it difficult to differentiate between the two in terms of performance.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}

model/llava/eval/table/review/review_gpt35_vicuna-13b.jsonl

@@ -1,80 +0,0 @@
-{"review_id": "jyhS7AFj2mrFNqoRXQJDPS", "question_id": 1, "answer1_id": "BZGowHM7L3RvtWRktKZjLT", "answer2_id": "cV4zXygaNP6CXEsgdHMEqz", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information on improving time management skills. Assistant 1 provided a slightly more detailed response, including tips on minimizing distractions, learning to say 'no', and delegating tasks. Assistant 2 also provided useful tips, but the response was not as comprehensive as Assistant 1's. Both assistants emphasized the importance of setting goals, using a calendar or planner, and taking breaks. Overall, both responses were helpful, but Assistant 1's response was slightly more detailed and comprehensive.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "NVTHESK8sQGgYq5RmQTpMr", "question_id": 2, "answer1_id": "GsrPLfiNEcRDYAC5aUoY23", "answer2_id": "3zpPUeoVsPWXtKMV7cAhZ6", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question about effective ways to deal with stress. Both answers included similar suggestions such as exercise, relaxation techniques, sleep, healthy diet, social support, time management, and seeking professional help. The level of detail in both responses was sufficient to provide a clear understanding of each strategy. Assistant 2 included an additional suggestion of relaxation techniques like progressive muscle relaxation, aromatherapy, and massage, which slightly enhanced the response. However, both assistants performed exceptionally well, and their answers were equally informative and helpful.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "fDwSXjgkma7Gu4b8QGUaCY", "question_id": 3, "answer1_id": "5SGfexmPoJTWoVbPMB87KB", "answer2_id": "6xpiZJE4vxxGqjRogPfBk7", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about the differences between Python and JavaScript. Assistant 1 provided a more structured response, covering programming paradigms, syntax, typing, and application areas, which made it easier to understand the key differences. Assistant 2 also covered similar points but included additional information about error handling, libraries, and speed. However, Assistant 2's response was slightly less organized, making it a bit harder to follow. Both assistants provided a good level of detail, but Assistant 1's response was more concise and easier to understand, which is why it receives a slightly higher score.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "cJw4V6atyX2JHA4FZM6Qc3", "question_id": 4, "answer1_id": "RcqQg364kgCkYPshqvmGSp", "answer2_id": "abitTVu2Dz8rdMxyThvFyJ", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information on increasing productivity while working from home. Assistant 1 offered a slightly more detailed response with 8 tips, while Assistant 2 provided 7 tips. Both assistants covered similar points, such as creating a dedicated workspace, setting a schedule, eliminating distractions, getting dressed, and taking breaks. However, Assistant 1 included the additional points of making a to-do list, challenging oneself, and staying positive, which contributed to a more comprehensive answer. Assistant 2's response was also well-rounded, but slightly less detailed compared to Assistant 1.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "2ZMgfaT49yqAiA3GYLNfp4", "question_id": 5, "answer1_id": "3R9jAndzLHQqJwmMi5mNox", "answer2_id": "UMZod8JaWia9KB2EVXdYrF", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate explanations of the basics of quantum computing. Assistant 1's response was slightly more detailed, covering different technologies used to build quantum computers and mentioning the importance of quantum computing in solving problems that are intractable for classical computers. Assistant 2's response was also informative, but it focused more on different approaches to building quantum computers rather than the broader context of quantum computing. Both responses were well-structured and informative, but Assistant 1's answer was more comprehensive, which is why it receives a slightly higher score.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Wz7U3tcQhAMK6HgLPwM7C3", "question_id": 6, "answer1_id": "Uw8SaYLPMGR5sdV9FDx8pb", "answer2_id": "WXRCqF34f4UUJzd3xbgAqT", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information regarding the differences between plant-based and animal-based protein sources. Assistant 1 provided a slightly more concise response, while Assistant 2 provided a more detailed response with a numbered list of differences. Assistant 1 mentioned the importance of animal-based protein sources for athletes and individuals with higher protein needs, which was a useful addition. Both assistants discussed the nutritional value, absorption, sustainability, health effects, and ethical considerations of the two types of protein sources. However, Assistant 1's response was more precise and to the point, making it easier to understand and digest the information, which is why it receives a slightly higher score.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "M3Yd3jLJrBzHL2KmmaiLmX", "question_id": 7, "answer1_id": "53gmokt2KBgKu6NMPopxcu", "answer2_id": "JREJbG5ZKXCNMoWoiJQxbC", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question about developing critical thinking skills. Both answers included practical tips and strategies for improving critical thinking, such as asking questions, analyzing information, considering different perspectives, and practicing logic and reasoning. Both responses were detailed and well-organized, making it easy for the user to understand and apply the suggestions. The only minor difference is that Assistant 2 included a few additional tips, such as engaging in debates and practicing mindfulness. However, both answers are equally valuable and informative, so they both receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "D4dXgsgoBdNwqUxxpmUkmp", "question_id": 8, "answer1_id": "bKrbrGsN7zjKLvBk2h3tvo", "answer2_id": "mmVwmX6TGJ2Y72gCNac4EQ", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question about the major challenges faced by the education sector today. Assistant 1 provided a clear list of seven challenges, while Assistant 2 expanded on these and included an additional challenge, making their response slightly more detailed. Both assistants covered important aspects such as access to education, funding, teacher shortages, technological integration, student engagement, and assessment. Assistant 2 also addressed equity and inclusion, as well as sustainability, which added value to their response. Overall, both assistants performed well, but Assistant 2 provided a more comprehensive answer.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "ntSaBiMeRMC82i2S2wkHh6", "question_id": 9, "answer1_id": "HEGL3aPUnNrdNtNt3XLDKi", "answer2_id": "DMTZyzd4rRAFV43xtBJ9ns", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. They both covered the primary factors that influence consumer behavior, such as personal, psychological, social, and marketing factors. Assistant 1 mentioned situational factors, while Assistant 2 included economic and product/service factors. Both answers were detailed and informative, and it is difficult to determine which one is superior, as they both provide valuable insights. Therefore, both assistants receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "eTBH8zoQhZfYYCAhQh4moS", "question_id": 10, "answer1_id": "W9zpMVa2cJUJW8B2uGMCJy", "answer2_id": "dETAsj4xHnUCSTkZezz8aM", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question about effective strategies for conflict resolution in the workplace. They both covered essential strategies such as active listening, clear communication, problem-solving, and seeking outside help or mediation if necessary. The level of detail in both responses was sufficient to understand the strategies and apply them in a workplace setting. Both assistants performed well, and it is difficult to differentiate their performance, so they both receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Y6cDAMFAEauqwsaGdHoraf", "question_id": 11, "answer1_id": "LacdmoweqKYGzt3aMBYjEa", "answer2_id": "C8ksZxg3LshMUWiLxPanbt", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information regarding the implications of using single-use plastic bottles versus reusable bottles on the environment and human health. Assistant 1's response was slightly more detailed and organized, with clear distinctions between environmental and health implications for both single-use and reusable bottles. Assistant 2 also provided valuable information, but the response was not as well-structured, and some points were not as clearly explained as in Assistant 1's response. Overall, both assistants performed well, but Assistant 1 had a slight edge in terms of clarity and organization.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "evnANWPnvUJ89vxV3sRZ7M", "question_id": 12, "answer1_id": "JqVreebbPuNdjw8E8K4Ssf", "answer2_id": "NeHhRc5P5uAU8eWSJBRkhG", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information in their responses. Assistant 1's response was slightly more detailed, covering a broader range of factors such as sensory inclusivity and employee training, which were not mentioned by Assistant 2. Assistant 2's response was also comprehensive, but it lacked the mention of sensory inclusivity and employee training. Both assistants provided valuable information on accessibility features, route design, scheduling, and affordability. Overall, Assistant 1's response was slightly more detailed and comprehensive, earning a 9, while Assistant 2's response was also strong but slightly less detailed, earning an 8.5.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "7X5LTBTBncxNXwdhDvknWG", "question_id": 13, "answer1_id": "hEMThhsN85Ud5X8xBv9BZJ", "answer2_id": "KAJ7UVwu8oCKyxZj9j82pm", "text": "9 8.5\nBoth assistants provided helpful, relevant, and accurate information about fiscal and monetary policies to combat economic recessions. Assistant 1's response was slightly more structured and concise, making it easier to understand the key points. Assistant 2's response was also informative and detailed, but the structure was less clear, and some points were repetitive. Both assistants covered the main aspects of fiscal and monetary policies, but Assistant 1's response was more precise and well-organized.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "7FK5fbRY6p2ep2MpPjv3yH", "question_id": 14, "answer1_id": "BvFV7sx53PAK5bNn89urFs", "answer2_id": "NnWfaeRe8PmitgmV4u5fY8", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a clear explanation of how language and cultural barriers can impact communication and relationships in multicultural societies, and also mentioned the importance of language classes, cultural exchange programs, and sensitivity training. Assistant 2 provided a more detailed response, discussing specific aspects of communication and relationships that can be affected by language and cultural barriers, such as cultural norms, stereotypes, prejudice, and power dynamics. While both answers were informative, Assistant 2's response was slightly more comprehensive, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "csv7uSp3JKQTDajTge3gCW", "question_id": 15, "answer1_id": "dM5GHbLuPNfzUbBnJz6w7K", "answer2_id": "WiGpqKRRwWonwgU95piNNc", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided relevant and helpful responses to the question. Assistant 1 focused on a specific scenario involving AI-powered chatbots for patient triage and automating routine tasks, which was a clear and concise example. Assistant 2, on the other hand, provided a broader overview of various ways AI could improve healthcare delivery, including data analysis, automating tasks, remote monitoring, personalized treatment plans, and speeding up research and development. Assistant 2's response was more comprehensive and covered a wider range of applications, which is why it received a slightly higher score. Both responses were accurate and detailed, but Assistant 2's answer provided a more extensive understanding of AI's potential impact on healthcare.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "AusuMoEsTd4zExWnGKz95b", "question_id": 16, "answer1_id": "BX7maaP5kGY6bBTLJRwkit", "answer2_id": "iangiZeex5ndxAXnWMrxBW", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about the process of gene editing using CRISPR-Cas9 technology, its potential applications, and ethical implications. Assistant 1 provided a slightly more detailed response, discussing the potential for eugenics, unintended consequences, and issues of access and equity. Assistant 2 also covered the main points, but with a bit less detail on the ethical implications. Both assistants did a good job, but Assistant 1's response was slightly more comprehensive.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "dUmijornRYz6nnYGYnZtv2", "question_id": 17, "answer1_id": "STuX8oc7Gu3SN6EWzwpUpp", "answer2_id": "XnMRLphzYQX4QRNht7tbui", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, accurate, and detailed responses to the question. They both explained the concept of vaccinations and how they work to protect individuals and communities from infectious diseases. They also both provided a clear explanation of herd immunity and its importance in preventing the spread of diseases. The quality of the answers is quite similar, and both assistants deserve a high score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "nYNJvBeat7YrWwEeNjHZts", "question_id": 18, "answer1_id": "TFUUXWS7yn2u2b4n7eM3ZB", "answer2_id": "HZc37bwy646mRzbqSsDAob", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question. Assistant 1 gave a good overview of the role of social media platforms in news consumption and the implications of misinformation. However, Assistant 2 provided a more detailed response, discussing specific factors such as personalization, virality, amplification, filter bubbles, confirmation bias, and lack of fact-checking, which contributed to a better understanding of the issue. Therefore, Assistant 2 receives a slightly higher score due to the level of detail in their response.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "P4hakPhF7TKj55mTydH4NT", "question_id": 19, "answer1_id": "3yRq2XXPi83H7Rr5SZS9rE", "answer2_id": "iJrMatLrMdJyyqMx9uJ45a", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question. Assistant 1's response was slightly more detailed, offering specific examples and strategies for promoting healthier diets, such as imposing taxes on unhealthy foods and increasing funding for community gardens and farmers' markets. Assistant 2 also provided a good response, with clear examples of how cultural, social, and economic factors influence food choices. However, Assistant 2's response was slightly less detailed in terms of strategies for promoting healthier diets. Both assistants performed well, but Assistant 1's response was more comprehensive and actionable.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "GbEY9PMrmhDNm5XUB3AYmc", "question_id": 20, "answer1_id": "Sw34dAwQPCfGGotwRwhvtv", "answer2_id": "oVEHqDnDTEADZSFfKgFTZd", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, accurate, and detailed explanations of the process of natural selection and how it contributes to the evolution and adaptation of species. Assistant 1 focused on explaining the essence of natural selection and its role as a driver of evolution and adaptation, while Assistant 2 provided a more structured explanation with numbered steps. Both explanations complement each other and provide a comprehensive understanding of the topic. Therefore, both assistants receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "JJ6BtrjfFvmjA9nvyJvNCL", "question_id": 21, "answer1_id": "cZw4Jw8Zyz6ZUy4WDsC6ta", "answer2_id": "WLAj4u59bj2oEXzahF79ek", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the user's question. They both included a sample introduction speech for a medieval knight at a royal banquet, emphasizing humility, loyalty, and service to the kingdom. The level of detail in both responses was appropriate and engaging. It is difficult to distinguish one as better than the other, as both responses effectively address the user's question, so they both receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "KNxHKpigcbEiptJeGiXtyd", "question_id": 22, "answer1_id": "nj9y2HTWFGsD5B278ozm73", "answer2_id": "fJPnM2XcRveW2zR4DDaeTb", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided relevant and engaging speeches to motivate a pirate crew to search for hidden treasure. Assistant 1's response was more concise and focused on the thrill of adventure and the rewards that await the crew. Assistant 2, on the other hand, started by clarifying that they do not condone piracy and then provided a speech that emphasized the challenges and the determination needed to succeed. Both speeches were well-crafted and detailed, but Assistant 1's response was slightly more direct and to the point, which is why it received a higher score.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "jsobbVWb4XgXruX5KGSAzP", "question_id": 23, "answer1_id": "Ep9rLcNzEGhG7AgbLTpRtm", "answer2_id": "fY4Xed6veWpcKfj5krZz8m", "text": "9 8\nBoth assistants provided relevant and creative soliloquies in the style of Shakespearean characters declaring their love. Assistant 1's soliloquy was slightly more engaging and used more vivid imagery, which made it stand out. Assistant 2's soliloquy was also well-written and relevant, but it lacked the same level of depth and emotional impact as Assistant 1's response. Both responses were accurate and detailed, but Assistant 1's soliloquy had a slight edge in terms of quality.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "nzQdRQqiGrCEPovYpkfcuq", "question_id": 24, "answer1_id": "oNULT72cYUvit7D9SHb5aM", "answer2_id": "LqFJA2JQbBXP77nkYjtrZK", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the user's question. They each shared their origin stories in a way that would be understandable and engaging for a curious child. Assistant 1 focused on the transformation from an ordinary person to a superhero, emphasizing the importance of courage and helping others. Assistant 2 explained their creation as an advanced artificial intelligence, highlighting their strong moral compass and desire to help others. Both answers were detailed and well-rounded, making it difficult to choose one over the other. Therefore, both assistants receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "bxv7oJi28Yny5CpxYtTriN", "question_id": 25, "answer1_id": "TX86xjPKTk2UxWwV4e8zRK", "answer2_id": "WxCKcRstJPXTXnqEzSX3Hg", "text": "8 7.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about the technological advancements in the year 3000. Assistant 1's response was more concise and organized, with a clear list format and a brief explanation of each advancement. Assistant 2's response was also informative, but it lacked the same level of organization and clarity as Assistant 1's response. Additionally, Assistant 1 mentioned the eradication of diseases like cancer and Alzheimer's and the reversal of the aging process, which are significant advancements that Assistant 2 did not mention. Overall, both assistants provided valuable information, but Assistant 1's response was slightly more effective in conveying the information.", "score": [8.0, 7.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "93SEJYNg3w6FJDC6CCVf3s", "question_id": 26, "answer1_id": "e5YFb6PojDThkcZdSH8kpC", "answer2_id": "dgPJ7DvtFHD7mxtRwzM3vW", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided detailed and engaging descriptions of the winning play in the final seconds of a championship game. They both captured the excitement and tension of the moment, while also highlighting the skill and determination of the players involved. Both responses were relevant, accurate, and helpful in answering the user's question. It is difficult to differentiate between the two in terms of quality, as both responses were well-written and effectively conveyed the thrilling nature of the game's conclusion. Therefore, both assistants receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "dhy48WZaBT7h7XUmY4Kt3Y", "question_id": 27, "answer1_id": "NnkbyoNFRHay4toKTFfaeE", "answer2_id": "ADX83sWvjJkewJX6JmYUzQ", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided detailed, relevant, and engaging descriptions of their respective signature dishes. They both showcased their creativity and passion for cooking, as well as their attention to detail in the preparation and presentation of the dishes. Both responses were equally helpful, accurate, and detailed, making it difficult to differentiate between the two in terms of overall performance. Therefore, both assistants receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "WmyJQvRV2wheGgHifaTX8o", "question_id": 28, "answer1_id": "Gpb8MuNU3Pt7k93dpRN9WM", "answer2_id": "ihNG3rwsrt95NDhCAFeSDR", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided relevant and accurate information about the summit of Mount Everest and the emotions a climber might experience. Assistant 1 gave a good description of the summit and the challenges faced during the climb. Assistant 2, however, provided a more vivid and detailed description of the emotions and the view from the top, making their response slightly more engaging and informative. Both assistants acknowledged their limitations as AI language models, but Assistant 2's response was more aligned with the user's question, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "ZBjXjAUfmo636RD8ftGmoj", "question_id": 29, "answer1_id": "SYvkCCHBUZPd9DQuidZM8K", "answer2_id": "Gmhqf3z4LvVfwPNFJ89BKd", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the user's question. Assistant 1 provided a more structured response, listing the challenges faced by a Mars colonist and then describing the daily life and activities. Assistant 2 also provided a detailed response, focusing more on the daily routine and integrating the challenges faced within that routine. Assistant 1's response was slightly more comprehensive and organized, which is why it receives a higher score. However, both responses were informative and addressed the user's question effectively.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "m96t6EWjwebt3SBbVs8QKi", "question_id": 30, "answer1_id": "NjdsG8tYfrHMT5zGZPavk6", "answer2_id": "gSwkKJCn6qDnNZond2xVJ3", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided engaging and detailed responses to the user's question. They both described the character's survival strategies, allies encountered, and the importance of trust and instincts in a post-apocalyptic world. Both responses were relevant and accurate, with a good level of detail. It is difficult to differentiate between the two responses in terms of quality, as both assistants performed exceptionally well in addressing the user's question.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "RsFZsrSQGvqkU9qRu6MzeE", "question_id": 31, "answer1_id": "8eovAhyvrKJEMWiVdYzByH", "answer2_id": "8RaBeMjxx2bCp2GKWv7YiP", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the user's question. They both offered multiple ways to determine if a restaurant is popular among locals or mainly attracts tourists, and they explained why this information might be useful. The level of detail in both responses is sufficient to guide the user in making informed decisions about where to dine. It's difficult to differentiate the quality of the two responses, as they both cover similar points and provide valuable information. Therefore, both assistants receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Do5xK3swjiBBXLCSxCZrJv", "question_id": 32, "answer1_id": "nvyaGEveLWBaxgXzriB93d", "answer2_id": "C65PZkmAfFfWRs4bPhyKqg", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1's response was slightly more detailed, with a clear list of seven clues to look for, while Assistant 2 provided six clues. Both assistants covered similar points, but Assistant 1's response was more organized and easier to follow. Assistant 2's response was also helpful and relevant, but slightly less detailed and organized compared to Assistant 1. Overall, both assistants performed well, but Assistant 1 had a slight edge in terms of clarity and organization.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "6coRp7diG94jbQfxFa2NTw", "question_id": 33, "answer1_id": "3xU2t6Yvx9EWpqfqvinNfH", "answer2_id": "4so4HTEjgDZKTqNAgkHHQX", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. They both covered the main reasons why someone might choose to use a paper map or ask for directions instead of relying on a GPS device or smartphone app. The level of detail in both responses was sufficient to address the user's question. Assistant 1 provided a slightly more concise answer, while Assistant 2 elaborated a bit more on each point. However, both answers were of high quality and deserving of equal scores.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "neKDsPNtPp68GyPCK6C7wc", "question_id": 34, "answer1_id": "Mq6hzNziUxzQ2juPMDrv3h", "answer2_id": "FCYaiexEzdoLFPAwvTgDDm", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. They both mentioned key points such as body language, active listening, and follow-up as indicators of genuine interest in a conversation. Both responses were detailed and well-structured, making it easy for the reader to understand the points being made. It is difficult to differentiate between the two responses in terms of quality, as both assistants provided valuable information and covered the topic thoroughly. Therefore, both Assistant 1 and Assistant 2 receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "fsikYyNM5HZSFuwtez49zW", "question_id": 35, "answer1_id": "KU6BNNN8d6MLHyrA8nV4DB", "answer2_id": "76EPQDh4ZNxBMGqED9LEFi", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, accurate, and detailed responses to the question. They both listed several reasons why someone might prefer to shop at a small, locally-owned business instead of a large chain store, even if the prices are higher. The reasons provided by both assistants were similar, with some slight variations in wording and the order of the points. Both responses were well-structured and easy to understand, making it difficult to differentiate between the two in terms of quality. Therefore, both assistants receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "6U9bZZbDKJLudgPjSVUJ6m", "question_id": 36, "answer1_id": "RpHbPLJamuknRRa3xU5bUF", "answer2_id": "cvBg3gyCyDuyESof3YXhTE", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question. Assistant 1's response was slightly more detailed and organized, with a clear list of factors to consider when assessing the credibility of a source. Assistant 2's response also provided valuable information, but it was less structured and had some overlap with Assistant 1's points. Both assistants emphasized the importance of checking the author's credentials, publication reputation, objectivity, and supporting evidence. Assistant 1 also mentioned evaluating the tone and verifying the information using reputable sources, which added value to their response. Overall, both assistants performed well, but Assistant 1's response was slightly more comprehensive and well-organized.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "UUzrSYFRn2RZDBvpse2Bvg", "question_id": 37, "answer1_id": "AFR3AJW4sSPLDLiAUvrL8s", "answer2_id": "kRgfUJ7qqkyZUnLd2fnnaX", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a good general overview of the factors that may influence individual preferences for fear-inducing experiences, while Assistant 2 provided a more detailed list of possible explanations, including brain chemistry, life experiences, personality traits, cultural factors, and learning. Assistant 2's response was slightly more comprehensive and informative, which is why it received a higher score. However, both responses were of high quality and addressed the question effectively.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Pi4zzV2gr6xqvZdLZJEU7k", "question_id": 38, "answer1_id": "esqiBYHa56ygcPU2ux2Pdx", "answer2_id": "J3YuizKcHQ74ydNyCcwgwu", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 provided a more detailed response, offering specific examples of how observing behavior can provide clues about cultural norms and expectations, such as dress codes, social hierarchy, communication styles, and customs and traditions. Assistant 2 also provided a relevant answer, discussing the importance of observing behavior to understand cultural norms, but provided fewer specific examples. Both answers were useful, but Assistant 1's response was more comprehensive and detailed, which is why it received a higher score.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "eADSQUs3wpe48gow6zcWUf", "question_id": 39, "answer1_id": "NmuuKUipqt62QKuEHCuBWh", "answer2_id": "abWLpFojLpNPfDGHpuRSUG", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided thoughtful, nuanced, and detailed answers to the question. They both acknowledged the complexity of the issue and presented arguments for both sides, highlighting the benefits and risks of space exploration and addressing Earth's problems. Both assistants emphasized the importance of personal values and priorities in making a decision on this topic. The quality of the answers is very similar, and both assistants deserve a high score of 9 for their performance.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "PZv2G3p5PXWEXDQNRgzUJL", "question_id": 40, "answer1_id": "3HypDqXt6tHieMDN7hWYCh", "answer2_id": "Ki4fkJvsoSxuQeSoj2AcBG", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. They both emphasized the importance of striking a balance between job creation and technological progress. Assistant 1 provided examples of methods for promoting job creation, while Assistant 2 went a step further by discussing policies and programs aimed at creating new jobs in industries less susceptible to automation and retraining programs for displaced workers. Assistant 2 also mentioned the benefits of technological progress in various sectors, such as healthcare, transportation, communication, and energy production. This additional information and the more comprehensive approach give Assistant 2 a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "F3bgdb6Q7KPRcx5fkXYSDp", "question_id": 41, "answer1_id": "DmQtupeyNDrQFBccBRAsbD", "answer2_id": "GRQjYgAapNAVqzuZR4KQpf", "text": "7 5\nAssistant 1 provided a more accurate and detailed response, considering the average blink rate, waking hours, and lifespan. The explanation was clear and easy to follow. Assistant 2, on the other hand, made an error in calculating the number of blinks per day and provided a less accurate estimate. Additionally, Assistant 2's response was less organized and harder to follow.", "score": [7.0, 5.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "hAGDMdzkakkM7ZNFj4Se6h", "question_id": 42, "answer1_id": "froHv7kwRMYGWPXDQXk2Gw", "answer2_id": "SB5a2AiK224hB927vkqvYs", "text": "9 6\nAssistant 1 provided a more accurate and detailed response, using the average weight of a grain of salt and the molar mass of NaCl to calculate the number of atoms in a grain of salt. The explanation was clear and easy to follow, and the final result was reasonable. Assistant 2, on the other hand, made an incorrect assumption that the grain of salt is a sphere and used the diameter to calculate the volume. Additionally, the calculation of the concentration of atoms per unit volume was incorrect, leading to an inaccurate final result. While Assistant 2's response contained some useful information, it was less accurate and less helpful than Assistant 1's response.", "score": [9.0, 6.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "SuUVSbhzMDWFbSdwBEn7Si", "question_id": 43, "answer1_id": "ahktv9NqxZ2cYquTXwF42r", "answer2_id": "4XYycBrMiJgYKPof2P6xoe", "text": "9 7\nAssistant 1 provided a more detailed and step-by-step explanation of how the estimated number of lightning strikes per day was calculated, taking into account the number of thunderstorms, the percentage that produce lightning, and the average number of strikes per thunderstorm. The final estimate of 1,972,600 lightning strikes per day was also accompanied by a note that some estimates range from 6 million to 100 million, acknowledging the variability in the data. Assistant 2, on the other hand, gave a more general explanation and provided an estimate of 100,000,000 lightning strikes per day without a clear calculation process. While both answers were relevant and accurate to some extent, Assistant 1's response was more helpful, precise, and detailed, which is why it received a higher score.", "score": [9.0, 7.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "kYsPQzYx3t8JAwKkNgXUZH", "question_id": 44, "answer1_id": "kqqPRaFqb3w9Ky9LGB3yKU", "answer2_id": "fpoXWHHdpv7XNBTS2NRY6d", "text": "8 7\nAssistant 1 provided a more detailed and step-by-step explanation of the calculations needed to estimate the number of balloons required to lift a house like in the movie \"Up.\" They considered the weight of the house, the lifting capacity of a single balloon, and the total lifting capacity needed. They also acknowledged the limitations of the calculation, such as the weight of the balloon material and the need for proper organization to lift the house evenly. Assistant 2, on the other hand, provided a less detailed explanation and used different assumptions for the weight of the house and the lifting power of the balloons. While both assistants concluded that it is not feasible to lift a house with balloons in real life, Assistant 1's response was more helpful, relevant, and accurate due to the detailed calculations and considerations provided.", "score": [8.0, 7.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "dqbgKEeqNCuuTBhg5ovqfJ", "question_id": 45, "answer1_id": "946tQg8kS7GYPSm4qcV6Pt", "answer2_id": "GRXWdnzLLzmeZRU67PMTb7", "text": "8 6\nAssistant 1 provided a more helpful and detailed response by offering an estimate of the number of text messages sent globally in a minute, which was the main focus of the question. The assistant also explained the calculation process and acknowledged that the number is an estimate and may vary due to different factors. Assistant 2, on the other hand, focused on the difficulties of determining the exact number of text messages sent in a minute and did not provide an estimate or a calculation. While Assistant 2's response was relevant and accurate in terms of the challenges in tracking text messages, it did not directly address the user's request for an explanation of the reasoning behind an estimate.", "score": [8.0, 6.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "DeEzTYEsG2B8nubmhaF4qc", "question_id": 46, "answer1_id": "cU3wut3Ta3ySbRHGxfwgjc", "answer2_id": "RTxk2jYsjYiiWMwcRjmfwu", "text": "8 6\nAssistant 1 provided a more detailed and step-by-step explanation of the estimation process, using a reasonable assumption of 2,000 words per person per day and explaining the limitations of the estimate. Assistant 2's estimate of 10,000 to 20,000 words per person per day seems too high, and the final estimate of 100 billion words per day is significantly lower than Assistant 1's estimate. Assistant 1's response is more helpful, relevant, and accurate, while Assistant 2's response is less detailed and less accurate.", "score": [8.0, 6.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "nvDTZFCrXe6NSdcFqYWJDv", "question_id": 47, "answer1_id": "hQP784Ch2yq2b3BaXVBVX3", "answer2_id": "2J2Et6W8u2kXLTUgfYrPxe", "text": "8 7\nBoth Assistant 1 and Assistant 2 provided helpful and relevant information in their responses. Assistant 1 gave a more precise estimation of the number of snowflakes by referring to the average snowfall in the United States and considering the size and shape of snowflakes. Assistant 2, while providing a detailed explanation of the factors affecting snowflake formation, did not provide a clear estimation of the number of snowflakes. Assistant 1's response was more focused on answering the question, while Assistant 2 provided more background information. Both responses were accurate and detailed, but Assistant 1's answer was more relevant to the question, which is why it received a higher score.", "score": [8.0, 7.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "3S8Z26nA4rbyND5nJKqFWo", "question_id": 48, "answer1_id": "a92bStUFdq4LBcv3pa9y3Z", "answer2_id": "nSGoG9Z5g5VuCXgmQJJKrq", "text": "8 7\nAssistant 1 provided a more detailed response, including an estimation of the total number of books ever written and the average number of pages per book. Assistant 1 also acknowledged the limitations of the estimation and the fact that new books are being written and published every day. Assistant 2's response was also relevant and helpful, but it provided a lower estimate for the total number of books ever published and did not mention the limitations of the estimation as clearly as Assistant 1. Both assistants provided reasonable estimates, but Assistant 1's response was more comprehensive and informative.", "score": [8.0, 7.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "d79neqK6LiNCsSu7yiWNZY", "question_id": 49, "answer1_id": "a2QAcAm9wJeP2BpyWQnhot", "answer2_id": "ScqJdUq9n5bp9qPv5WPqG5", "text": "9 7\nAssistant 1 provided a clear and concise explanation, directly addressing the question and using the correct time frame of 3.8 billion years ago for the beginning of life on Earth. The answer was easy to follow and included a reasonable approximation of the number of orbits. Assistant 2, on the other hand, used the age of the Earth (4.5 billion years) instead of the beginning of life (3.8 billion years) for the calculation, which made the answer less accurate and relevant to the question. However, Assistant 2 did provide some additional information about the Earth's orbit, which added some value to the response. Overall, Assistant 1's response was more helpful, relevant, and accurate, while Assistant 2's response was less accurate but still provided some useful information.", "score": [9.0, 7.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "KFEzPSHMSp88iZ4MkBEPQQ", "question_id": 50, "answer1_id": "CrmusnxbTtGXF2varfcUd4", "answer2_id": "GdLFr88pCwsGpfRBRQQkyh", "text": "8 7\nBoth Assistant 1 and Assistant 2 provided relevant and helpful answers to the question, explaining that it is impossible to determine the exact number of songs recorded throughout history. Assistant 1 provided a more detailed response, discussing the oldest known musical instrument, the Library of Congress's collection, and the importance of considering non-Western music. Assistant 2 also mentioned the invention of recording technology and the rise of digital music but provided fewer specific examples and details. Therefore, Assistant 1 receives a score of 8, and Assistant 2 receives a score of 7.", "score": [8.0, 7.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "MaeeytBPffy2qXeTWAgVb3", "question_id": 51, "answer1_id": "J9pZp6z2UUW7YcXgzUouqs", "answer2_id": "Sa7uNEbFGRFuXBAwau8sHS", "text": "8 7\nBoth Assistant 1 and Assistant 2 provided relevant and thoughtful answers to the question. Assistant 1's response was more focused on the potential impact of the internet on the Renaissance period, discussing how it could have affected intellectual exchange, collaboration, and the democratization of knowledge. Assistant 2, on the other hand, emphasized the technological limitations of the era and the differences between the Renaissance and the digital age. While both responses were helpful and accurate, Assistant 1's answer was slightly more detailed and directly addressed the question, which is why it receives a higher score of 8, while Assistant 2 receives a 7.", "score": [8.0, 7.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "7YnF7KE5b7DmdJVd2CWhPg", "question_id": 52, "answer1_id": "67bYUQb6zru8ofiub7uNUi", "answer2_id": "T6Ar3cAEw3AmVVQTcCPp8N", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a good overview of the potential consequences of the Aztecs repelling the Spanish conquistadors, touching on the impact on the Aztec empire, the indigenous people of the Americas, and the potential interest of other European nations. Assistant 2, however, provided a slightly more detailed response, discussing the Aztec civilization's strengths, the potential resistance to European diseases, the possible maintenance of cultural and religious practices, and the potential for alliances with other indigenous groups. Both answers were informative, but Assistant 2's response was more comprehensive, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "bAfAwLcXniXktiqNsvDGFV", "question_id": 53, "answer1_id": "gAisnQTHWFLW8aa5fQPNJf", "answer2_id": "KiZQev5JEk2h6JYeQnFmtM", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided relevant, accurate, and detailed responses to the question. Assistant 1's response was slightly more helpful, as it touched upon the impact of the Black Death on the medical field, hygiene practices, and cultural landscape, which Assistant 2 did not mention. Assistant 2's response was still informative, discussing the potential effects on demography, economy, and society, but it lacked the additional context provided by Assistant 1.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "8vUuWHUHuEn2SUrzRcoV6v", "question_id": 54, "answer1_id": "4ZJCbj7T8BGzNhDqz7NSF4", "answer2_id": "cYiyYKKXM3GXkrZHAbX83S", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 focused on the potential impact of Newton's work on biology and the possible consequences for the field of physics. Assistant 2, on the other hand, provided a more detailed overview of Newton's contributions to various fields and discussed the difficulty in predicting the specific contributions he might have made to biology. Assistant 2's response was more comprehensive and provided a broader context, which is why it received a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "FCJoqPdZYVBmAfS3VjFCkC", "question_id": 55, "answer1_id": "c6ixri3qqLfSBBnwMkgYB7", "answer2_id": "PQmMUdAAcBsAWmWaTvdHSU", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant answers to the question. Assistant 1 focused on the overall impact of the Beatles on music and society, while Assistant 2 went into more detail about the possible outcomes if the Beatles had never formed. Assistant 2's answer was more comprehensive, offering specific scenarios and covering various aspects of the music industry and culture, which is why it received a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "bSZUNocHnjSSsxyUBMSUMu", "question_id": 56, "answer1_id": "c9AtDn7eeSYhtH854MQDDB", "answer2_id": "PorExChQ9VeYsPJptdgtsB", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 provided a slightly more detailed response, mentioning the impact of Turing's work on the development of computer technology and artificial intelligence, which adds value to the answer. Assistant 2, on the other hand, touched upon the possibility of alternative strategies and technologies being developed by the Allies, but did not go into as much detail as Assistant 1. Both assistants acknowledged the difficulty in predicting the exact outcome of the war without Turing's contributions, which is important to consider. Overall, both responses were informative and well-structured, but Assistant 1 provided a slightly more comprehensive answer.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "f3KTRaNot8TePqUPATMhRG", "question_id": 57, "answer1_id": "jYd2gg6MJH8hdqFSAJTaiR", "answer2_id": "249f6dSMwZRZVMmtxv6yDm", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 gave a clear overview of the consequences of not having the Suez Canal, touching on the impact on shipping routes, international trade, and the development of the region. Assistant 2, however, went into more detail about the longer and more treacherous route around the Cape of Good Hope, the impact on international trade, and the historical context of European colonization in Asia. Assistant 2 also mentioned the engineering and technological advancements required for the construction of the canal and its role in international conflicts. While both answers were informative, Assistant 2 provided a more comprehensive response, which is why it received a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "J5EKWhvGBjYM9kSttb7RBp", "question_id": 58, "answer1_id": "nZJ6LGJFegnHetutiAQtFm", "answer2_id": "nxa3m6kiAZwKgcMUBY8KYz", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question. They both discussed the potential advancements in various fields such as science, technology, and governance that the Maya civilization could have made if they had not collapsed. Both assistants also mentioned the possible impact on the colonization of the Americas and the influence on neighboring civilizations. The level of detail in both responses is quite similar, and both assistants acknowledged the difficulty in predicting the exact outcomes. Therefore, both Assistant 1 and Assistant 2 receive a score of 9 for their overall performance.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "jEWD6eqwH9jscVgJKDNDUg", "question_id": 59, "answer1_id": "dmEgLyeYNcwBZWHBak6Lap", "answer2_id": "DXFvhjCaKqQiBsFDCkXGMT", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question. Assistant 1 mentioned the Vikings and the possibility of indigenous peoples from Asia migrating to the Americas, while Assistant 2 focused more on the potential consequences of Columbus not discovering the Americas. Assistant 2's response was slightly more detailed and provided a clearer picture of the potential impact on the world, which is why it received a higher score. However, both responses were informative and addressed the question well.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "RG6quoUjP9RfEhB7SBeQWU", "question_id": 60, "answer1_id": "bkuECkuy7YiDUcj9oJjdrZ", "answer2_id": "BCUK5VcpZK26jMJ2UMgR3E", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the question. Assistant 1 went into more detail about the potential impact on van Gogh's personal life, such as his mental health and financial situation, as well as the broader implications for art history. Assistant 2 also discussed the potential impact on van Gogh's art and personal life but did not delve as deeply into the broader implications for art history. Both assistants provided a well-rounded response, but Assistant 1's answer was slightly more detailed and comprehensive, which is why it received a higher score.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "KKYYAMWpuxxqpPCxYRjr3s", "question_id": 61, "answer1_id": "2PRjT7j3V6487xZREfQfuD", "answer2_id": "JHTKBrLVTp7bv5zW2uwYVW", "text": "8 6\n\nAssistant 1:\nStrengths:\n- The code is well-structured and easy to read.\n- The function `count_occurrences()` is modular and can be reused.\n- Proper error handling is implemented when opening the file.\n- The code handles case sensitivity by converting the text to lowercase.\n- Comments are clear and concise, explaining the code's logic and functionality.\n\nWeaknesses:\n- The code does not handle punctuation marks and special characters when comparing words.\n\nSuggestions for improvement:\n- To handle punctuation marks and special characters, you can add a function to remove them from the words before comparing them with the search word.\n\nAssistant 2:\nStrengths:\n- The code is simple and easy to understand.\n- The program uses the `find` function to search for the given word in each line.\n\nWeaknesses:\n- The code does not handle case sensitivity.\n- The code does not handle punctuation marks and special characters when comparing words.\n- The code does not count multiple occurrences of the word in the same line.\n- The code lacks comments explaining the logic and functionality.\n- The code is not modular, making it harder to reuse the counting functionality.\n\nSuggestions for improvement:\n- To handle case sensitivity, convert the text and search word to lowercase before comparing.\n- To handle punctuation marks and special characters, remove them from the words before comparing them with the search word.\n- Use a loop to count multiple occurrences of the word in the same line.\n- Add comments to explain the code's logic and functionality.\n- Consider creating a separate function for counting occurrences to improve modularity.", "score": [8.0, 6.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "Be9fbF7prWfkJiLcaRNjLP", "question_id": 62, "answer1_id": "jWyN8NTdVix6CUoqfbRqVx", "answer2_id": "jyzD2deb9JAffRhhkk37r5", "text": "8 4\n\nAssistant 1:\nStrengths:\n- The code is well-structured and easy to understand.\n- The implementation correctly solves the problem using dynamic programming.\n- The comments are clear and concise, explaining the logic and functionality of the code.\n\nWeaknesses:\n- There are no comments explaining the initialization of the 2D array 'm'.\n- The code could be more efficient by not initializing the 2D array with all zeros and then updating it.\n\nSuggestions for improvement:\n- Add comments to explain the initialization of the 2D array 'm'.\n- Consider initializing the 2D array 'm' with the appropriate values instead of all zeros.\n\nAssistant 2:\nStrengths:\n- The code is structured and readable.\n- The implementation attempts to solve the problem using dynamic programming.\n\nWeaknesses:\n- The code does not correctly implement the given problem statement, as it returns the minimum edit distance instead of the longest common subsequence.\n- The comments are not as clear and concise as they could be, making it harder to understand the code's logic and functionality.\n- The code initializes the 2D array with `float('inf')`, which is unnecessary and inefficient.\n\nSuggestions for improvement:\n- Modify the code to correctly implement the longest common subsequence problem.\n- Improve the comments to better explain the code's logic and functionality.\n- Consider initializing the 2D array with more appropriate values instead of `float('inf')`.", "score": [8.0, 4.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "nD8SHmwjdEoLfodK7i8a9f", "question_id": 63, "answer1_id": "mx9G7gfKTCXCmNRaiMZQr9", "answer2_id": "jPGHEfp7FxhDyvRA6qEN3j", "text": "8 8\n\nBoth Assistant 1 and Assistant 2 provided a working solution for validating email addresses using regular expressions in Python. Their code is accurate, efficient, and easy to understand. Both solutions are very similar, with only minor differences in variable names and print statements.\n\nStrengths:\n- Both solutions correctly implement the given problem statement.\n- The code is accurate and efficient in both cases.\n- Both solutions include clear and concise comments that explain the code's logic and functionality.\n\nWeaknesses:\n- Both solutions use a simple regular expression that may not cover all edge cases for email validation. However, this is acceptable for a basic email validation implementation.\n\nSuggestions for improvement:\n- Both solutions could benefit from a more comprehensive regular expression that covers more edge cases for email validation. However, this is not a requirement for the given problem statement.\n- Assistant 2's solution could be improved by wrapping the email validation code in a function, similar to Assistant 1's solution. This would make the code more modular and reusable.", "score": [8.0, 8.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "H9nS4Gsoe6nK5q2ebuhRk7", "question_id": 64, "answer1_id": "8LjpXk6Va5L2FBEwTU9YJ6", "answer2_id": "Ra9eTcAuNZPkPRnaHiQrak", "text": "8 4\n\nAssistant 1:\nStrengths:\n- The code is simple and easy to understand.\n- The dynamic programming approach is implemented correctly using a list to store Fibonacci numbers.\n- The code is efficient and will work well for large values of n.\n- The example usage is helpful for understanding the function's usage.\n\nWeaknesses:\n- The code could benefit from more comments explaining the logic and functionality.\n\nSuggestions for improvement:\n- Add comments to explain the logic and functionality of the code.\n\nAssistant 2:\nStrengths:\n- The code attempts to use dynamic programming with a memoization table.\n- The base case for n = 0 and n = 1 is handled correctly.\n\nWeaknesses:\n- The code does not actually use the memoization table, making it inefficient for large values of n.\n- The recursive calls to the function do not use the memoization table, leading to redundant calculations.\n- The code structure is more complex than necessary.\n\nSuggestions for improvement:\n- Use the memoization table to store and retrieve previously calculated Fibonacci numbers.\n- Simplify the code structure by removing the unnecessary memoization table initialization and using a list to store Fibonacci numbers, similar to Assistant 1's approach.", "score": [8.0, 4.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "AeohqWsGLDJmqX83xZmNPF", "question_id": 65, "answer1_id": "BLC8fhAUeahFfrjBRiL9tx", "answer2_id": "5mbEFLEnEx8Cm2wEF8WAbM", "text": "9 8.5\n\nBoth Assistant 1 and Assistant 2 provided correct and efficient implementations of the binary search algorithm. Their code is readable and well-structured. However, there are a few differences in their submissions.\n\nAssistant 1:\n- The code is clear and easy to understand.\n- The example usage provided is helpful for understanding how to use the function.\n- The variable names \"left\" and \"right\" are more descriptive than \"start\" and \"end\" used by Assistant 2.\n\nAssistant 2:\n- The code is also clear and easy to understand.\n- The explanation of the algorithm is more detailed, which is helpful for understanding how the algorithm works.\n- The variable names \"start\" and \"end\" are less descriptive than \"left\" and \"right\" used by Assistant 1.\n\nSuggestions for improvement:\n- Assistant 1 could provide a more detailed explanation of the algorithm, similar to Assistant 2.\n- Assistant 2 could use more descriptive variable names, such as \"left\" and \"right\", as used by Assistant 1.\n- Both assistants could add comments within the code to explain the logic and functionality of each step.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "PhJVYMN4t8GbM7hsxJm47V", "question_id": 66, "answer1_id": "NAH245JGvMWF24FWZJagYp", "answer2_id": "KLbBzjbuwq4agAESQ9Wfpq", "text": "8 5\n\nAssistant 1:\nStrengths:\n- The code is well-structured and easy to read.\n- The implementation is correct and efficient.\n- The comments are helpful and explain the code's logic and functionality.\n- The code adheres to proper coding standards and best practices.\n\nWeaknesses:\n- The code could benefit from a few more comments, especially for the `enqueue` and `dequeue` methods.\n\nSuggestions for improvement:\n- Add more comments to explain the logic behind the `enqueue` and `dequeue` methods.\n\nAssistant 2:\nStrengths:\n- The code is readable and has a clear structure.\n- The `peek` and `is_empty` methods are implemented correctly.\n\nWeaknesses:\n- The implementation of the `enqueue` and `dequeue` methods is incorrect, as it does not use two stacks to implement the queue.\n- The code does not adhere to proper coding standards and best practices, as it uses a mix of Python and C++ syntax.\n- The comments are not as helpful as they could be, and there are no comments for the `peek` and `is_empty` methods.\n\nSuggestions for improvement:\n- Correct the implementation of the `enqueue` and `dequeue` methods to use two stacks.\n- Ensure that the code uses consistent syntax, preferably Python syntax.\n- Add more comments to explain the logic behind the `peek` and `is_empty` methods.", "score": [8.0, 5.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "gJz8gj8qVa2Co9HSotcUUQ", "question_id": 67, "answer1_id": "NKXTwB3WtfFcmQZbTxBP5o", "answer2_id": "ganAwetd9VTzEAiTtsskzX", "text": "7 5\n\nAssistant 1:\nStrengths:\n- The code is easy to read and understand.\n- The function works correctly for the given problem statement.\n- The example provided is helpful for understanding the code's functionality.\n\nWeaknesses:\n- The code uses an extra data structure (the 'common' list) which is against the problem statement's requirement.\n- The nested loops can be inefficient for large arrays.\n\nSuggestions for improvement:\n- To avoid using an extra data structure, you can print the common elements directly instead of appending them to a list.\n- Consider using a more efficient algorithm, such as sorting the arrays and using two pointers to find common elements.\n\nAssistant 2:\nStrengths:\n- The code is easy to read and understand.\n- The example provided is helpful for understanding the code's functionality.\n\nWeaknesses:\n- The code uses an extra data structure (the 'result' list) which is against the problem statement's requirement.\n- The nested loops can be inefficient for large arrays.\n- The code does not handle duplicate elements in the arrays, resulting in duplicate common elements in the output.\n\nSuggestions for improvement:\n- To avoid using an extra data structure, you can print the common elements directly instead of appending them to a list.\n- Consider using a more efficient algorithm, such as sorting the arrays and using two pointers to find common elements.\n- Add a check to ensure that duplicate common elements are not printed.", "score": [7.0, 5.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "HnmQ6NkCSS8sumGzBnwkgo", "question_id": 68, "answer1_id": "5P7wPyrNwBrHNdJNrETS5h", "answer2_id": "LG6szQ3cqNRzUjXtZtXG94", "text": "First, I will solve the problem independently:\n\nf(x) = 5x^3 - 2x + 3\n\nf(2) = 5(2)^3 - 2(2) + 3\nf(2) = 5(8) - 4 + 3\nf(2) = 40 - 4 + 3\nf(2) = 39\n\nNow, I will evaluate the problem-solving process of Assistant 1 and Assistant 2:\n\nAssistant 1:\nf(2) = 5(2)^3 - 2(2) + 3\nf(2) = 5(8) - 4 + 3\nf(2) = 40 - 1\nf(2) = 39\n\nAssistant 2:\nf(2) = 5(2)^3 - 2(2) + 3\nf(2) = 5 * 8 - 2 + 3\nf(2) = 41 - 2 + 3\nf(2) = 40\n\nAssistant 1 has the correct answer and followed the correct steps. Assistant 2 made a mistake in the second step, where they incorrectly calculated 5 * 8 - 2 as 41 instead of 40. This led to an incorrect final answer of 40.\n\nScores:\nAssistant 1: 10\nAssistant 2: 6\n\nAssistant 1 performed better in this case.", "score": [10, 6], "reviewer_id": "gpt-4-0328-math", "metadata": {}}
-{"review_id": "c5XdU8rAprsY8V5j7CGAe2", "question_id": 69, "answer1_id": "UmnL4WoucBduFpX4jptkNU", "answer2_id": "LHMnXGbSZubeZJcr5fgrte", "text": "First, I will solve the problem independently:\n\n3x + 10 = 5(x - 2)\n\n3x + 10 = 5x - 10  (use the distributive property)\n\n-2x = -20 (subtract 3x from both sides)\n\nx = 10 (divide both sides by -2)\n\nTherefore, x = 10.\n\nNow, I will evaluate the problem-solving process of Assistant 1 and Assistant 2:\n\nAssistant 1:\nThe steps provided by Assistant 1 are correct, and the final answer is x = 10.\n\nAssistant 2:\nThe steps provided by Assistant 2 are incorrect. The assistant made an error in step 2 by subtracting 5x from both sides, which resulted in an incorrect equation. The rest of the steps are also incorrect due to this initial error.\n\nScores:\nAssistant 1: 10\nAssistant 2: 1\n\nAssistant 1 performed better and provided the correct solution to the problem.", "score": [10, 1], "reviewer_id": "gpt-4-0328-math", "metadata": {}}
-{"review_id": "3T6zyEyabtCSmED9WgtDSm", "question_id": 70, "answer1_id": "Hymm673GkY5tXNaTFeNUBZ", "answer2_id": "TGENVWL5iAYi4NCf5jAzKy", "text": "First, I will solve the problem independently:\n\nThe distance formula is given by:\n\ndistance = sqrt((x2 - x1)^2 + (y2 - y1)^2)\n\nPlugging in the coordinates of the given endpoints, we get:\n\ndistance = sqrt((10 - 2)^2 + (4 - (-2))^2)\ndistance = sqrt(8^2 + 6^2)\ndistance = sqrt(64 + 36)\ndistance = sqrt(100)\ndistance = 10\n\nNow, I will examine the problem-solving process of Assistant 1 and Assistant 2:\n\nAssistant 1:\nThe steps followed by Assistant 1 are correct, and the final answer is also correct.\n\nAssistant 2:\nThe steps followed by Assistant 2 are incorrect. The mistake occurs in the calculation of the differences between the coordinates:\n\nIncorrect: sqrt((10 - 2)^2 + (4 - (-2))^2) = sqrt(18^2 + 4^2)\nCorrect: sqrt((10 - 2)^2 + (4 - (-2))^2) = sqrt(8^2 + 6^2)\n\nThe final answer provided by Assistant 2 is incorrect.\n\nScores:\nAssistant 1: 10\nAssistant 2: 4\n\nAssistant 1 performed better in this case, as they followed the correct steps and provided the correct answer. Assistant 2 made a calculation mistake in the distance formula, leading to an incorrect answer.", "score": [10, 4], "reviewer_id": "gpt-4-0328-math", "metadata": {}}
-{"review_id": "2FNQ97Hnop7zu525REHpPh", "question_id": 71, "answer1_id": "PUzddJ35E3WsM7BDQ9E59i", "answer2_id": "kc9oytarvqyNVVfGZz93EL", "text": "9 9.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the user's request for a formal email proposing a joint venture. Both responses included appropriate greetings, introductions, and explanations of the proposed partnership. Assistant 2's response was slightly more detailed, including the proposal of establishing a new jointly-owned company and suggesting a meeting to discuss the proposal further. However, both responses were of high quality and would be useful to the user.", "score": [9.0, 9.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "jbBS3mJXgYxGnnjhamALro", "question_id": 72, "answer1_id": "6Q72hZCtDkgq379yhdmN5N", "answer2_id": "NxstpvVEnGMny3jECtvrw2", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate resignation letter samples. They both addressed the user's request to leave on good terms and express gratitude for the opportunities provided. The level of detail in both responses is appropriate, and both letters are well-structured and professionally written. It is difficult to differentiate between the two responses in terms of quality, as both are excellent examples of resignation letters.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "TzDXKHsob9xTKFdvCMvyVn", "question_id": 73, "answer1_id": "ReXnHy9C8SwcYPAep6gvJg", "answer2_id": "XN9NBpeQJiQqGT5UYkys7N", "text": "9 9\n\nBoth Assistant 1 and Assistant 2 provided well-structured, detailed, and relevant formal letters of recommendation for a student applying to a prestigious graduate program in computer science. Both letters included essential elements such as the sender's and recipient's information, a clear introduction, a thorough explanation of the student's academic achievements, and a strong conclusion. Both letters were accurate, relevant, and helpful in addressing the user's request. Therefore, I believe both assistants deserve a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "X2tMhW8rQLckXYViCjz5ZM", "question_id": 74, "answer1_id": "cKk5zZe8yYY4JH3kr5pGXG", "answer2_id": "3qMqAZcfHUVUTEJnMXT8Pw", "text": "8 9\nBoth assistants provided relevant and detailed responses to the user's request. Assistant 1's email was well-structured and included benefits and features of the software solution, as well as a special introductory offer. However, Assistant 2's response was slightly more precise, as it mentioned the target audience and market, and provided a clearer list of key features. Additionally, Assistant 2's email was more personalized by mentioning the company name and offering a demo. Both emails were helpful and accurate, but Assistant 2's response was more comprehensive and tailored to the user's request.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "EcpwAYWnZD8YF8kvKNAwBy", "question_id": 75, "answer1_id": "c5rwA3cPjytSGcn7H8dZ6Q", "answer2_id": "hMXjd228Mc8pnc7zgd2frG", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate responses to the user's question. Assistant 1's response was slightly more detailed, including information about the cause of the delay, the steps taken to resolve the issue, and measures to prevent future delays. Assistant 2's response was also well-written and addressed the issue, but it lacked the specific details about the cause and resolution that Assistant 1 provided. Overall, both responses were of high quality, but Assistant 1's response was more comprehensive and informative.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "LQhfYPFfLcwFPAb5KCJzmS", "question_id": 76, "answer1_id": "XZGPtBo86KfF9REZ36s2X5", "answer2_id": "gUEd9nNepqy8nsfbypscHx", "text": "9 8\nAssistant 1 provided a well-structured script for a YouTube video, including visual cues and narration, which made it more engaging and informative. The response covered the origins of jazz, its evolution, and its cultural significance, as well as mentioning jazz festivals and clubs. Assistant 2 also provided a good response, discussing the history and cultural significance of jazz, its influence on other genres, and its role in the civil rights movement. However, Assistant 2's response was less engaging and lacked the visual cues and structure of a video script, which is why Assistant 1 received a higher score. Both responses were relevant, accurate, and detailed, but Assistant 1's response was better suited for a YouTube video script.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "M8dSLebM2csXbgXd5r59X2", "question_id": 77, "answer1_id": "DRncHCsdGji756efDhacUT", "answer2_id": "nZZyn3SAvU8T2BVR73LMHC", "text": "9 9\nBoth Assistant 1 and Assistant 2 provided engaging and well-written travel blog posts about a recent trip to Hawaii. They both highlighted cultural experiences, such as attending a luau and watching hula performances, and must-see attractions like Waikiki Beach and Haleakala National Park. The level of detail and accuracy in both responses was excellent, and both assistants effectively conveyed the excitement and beauty of a trip to Hawaii. It is difficult to choose one over the other, as both responses were equally helpful, relevant, and engaging. Therefore, both assistants receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "APtBcAMY9tVW7nyE4g2ZAA", "question_id": 78, "answer1_id": "Y5rCQHHDA6WNfhRcB6QboG", "answer2_id": "YM4qjUM5VfmWnzM3HXRB4G", "text": "9 8.5\nBoth Assistant 1 and Assistant 2 provided captivating movie reviews for a recently released science fiction film. Assistant 1's response was slightly more detailed and engaging, with a more in-depth discussion of the plot, characters, and special effects. The review also mentioned the character development and growth throughout the film. Assistant 2's response was also well-written and engaging, but it was slightly less detailed in comparison. Both reviews were relevant, accurate, and helpful, but Assistant 1's response had a slight edge in terms of depth and detail.", "score": [9.0, 8.5], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Z5Rhru7as3Yhk8ZXjzfPe4", "question_id": 79, "answer1_id": "Lea4wh5n6GsEkBnKsntN64", "answer2_id": "WcbzNkzu5q66QkK92NxmGB", "text": "9 8\nAssistant 1 provided a well-structured podcast script with clear sections, covering the music industry before streaming, the rise of streaming platforms, their impact on artists and the industry, and the future of music streaming. Assistant 2 also provided a good podcast script, but it was less detailed and structured compared to Assistant 1. Assistant 1's response was more comprehensive and organized, making it easier to follow and understand the flow of the podcast.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "kw3p4X9zBGtVDfPDRoJwRE", "question_id": 80, "answer1_id": "gdLxzcypTeuD6ToC6HWnXh", "answer2_id": "Tfm4f2mbpKJsa8MT6exs8D", "text": "9 9\n\nBoth Assistant 1 and Assistant 2 provided well-written and detailed symphony concert reviews that discussed the orchestra's performance and the overall audience experience. Both reviews were engaging and captured the essence of a symphony concert, making it difficult to differentiate between the two in terms of helpfulness, relevance, accuracy, and level of detail. Therefore, both assistants receive a score of 9.", "score": [9.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}

model/llava/eval/table/review/review_llama-13b_vicuna-13b.jsonl

@@ -1,80 +0,0 @@
-{"review_id": "WFp5i5yjjFethrgugKTDmX", "question_id": 1, "answer1_id": "J3UA6eGXGyFeUGqGpP3g34", "answer2_id": "cV4zXygaNP6CXEsgdHMEqz", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question about improving time management skills. Assistant 1 offered a more detailed list of strategies, with 16 points, while Assistant 2 provided a slightly shorter list with 7 points. Both assistants covered similar topics, but Assistant 1 included additional suggestions such as managing stress, getting enough sleep, and striking a balance. Assistant 2's answer was well-structured and concise, but Assistant 1's response was more comprehensive, which is why Assistant 1 receives a 9 and Assistant 2 receives an 8.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "VFr7STcg4Yss7qHrgKZtJ2", "question_id": 2, "answer1_id": "jZVDNTtFnNNd6vgkGjzAGa", "answer2_id": "3zpPUeoVsPWXtKMV7cAhZ6", "text": "9 8\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate answers to the question about effective ways to deal with stress. Assistant 1 provided a more detailed response with 10 suggestions, while Assistant 2 provided 8 suggestions. Both assistants covered similar points, such as exercise, relaxation techniques, social support, and seeking professional help. Assistant 1, however, included additional suggestions like improving time management and developing a support network, which added more value to their response. Therefore, Assistant 1 receives a 9, and Assistant 2 receives an 8.", "score": [9.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "4cn29wYPaXYEyypZC5UBFh", "question_id": 3, "answer1_id": "NbSxRXf8Yuvjr7HC6AvrPw", "answer2_id": "6xpiZJE4vxxGqjRogPfBk7", "text": "4 8\nAssistant 1's response is repetitive and contains several incorrect statements, making it less helpful and accurate. Assistant 2's response is more concise, accurate, and relevant, providing a clear comparison between Python and JavaScript, which makes it more helpful and informative.", "score": [4.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "QfbSxZhq2a3unPfDqPXWzm", "question_id": 4, "answer1_id": "E9zrPDdncYvAebEaxiPXfx", "answer2_id": "abitTVu2Dz8rdMxyThvFyJ", "text": "8 9\nBoth assistants provided helpful and relevant tips for increasing productivity while working from home. Assistant 1's response was well-organized and concise, covering important aspects such as setting up a workspace, blocking distractions, taking breaks, avoiding multitasking, having an organized schedule, and setting goals. Assistant 2's response was more detailed and covered additional points such as getting dressed for work, scheduling meetings, and staying connected with colleagues and loved ones. While both responses were accurate and useful, Assistant 2's answer was more comprehensive and provided a slightly better level of detail, which is why it received a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "ZhokYAotAEkh6QQMkjJeDi", "question_id": 5, "answer1_id": "36TYpADDHAfRvtvKitfSXR", "answer2_id": "UMZod8JaWia9KB2EVXdYrF", "text": "7 9\nAssistant 1 provided a brief and simple explanation of quantum computing, mentioning the use of qubits and the advantage of quantum computers in solving certain problems more efficiently. However, the response lacked depth and details. Assistant 2, on the other hand, provided a more comprehensive explanation, covering the basics of quantum computing, the use of qubits, and the different approaches to building quantum computers. The response also mentioned potential applications of quantum computing, making it more informative and helpful overall.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "RWRpNF3RZiurzyAKHRggx4", "question_id": 6, "answer1_id": "8vtLLYRM352mZ8PXXbwzBT", "answer2_id": "WXRCqF34f4UUJzd3xbgAqT", "text": "8 10\nAssistant 1 provided a brief and accurate response, but it lacked details and only mentioned the difference in amino acid profiles. Assistant 2, on the other hand, provided a more comprehensive answer, discussing nutritional value, absorption, sustainability, health effects, ethical considerations, and cost. This made Assistant 2's response more helpful and informative, earning it a higher score.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "ngDhYdQ3bPkbvctvpoJoxJ", "question_id": 7, "answer1_id": "mrCniyWYvAtxWhgMdXq2BG", "answer2_id": "JREJbG5ZKXCNMoWoiJQxbC", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant information on how to develop critical thinking skills. Assistant 1 offered four suggestions, while Assistant 2 provided a more detailed list of ten tips. Both answers were accurate and relevant to the question. However, Assistant 2's response was more comprehensive and provided a wider range of strategies, which is why it receives a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "efxZ8mmetiunsqv5AVCcKD", "question_id": 8, "answer1_id": "S8fmdbvpvbgTUyDU9V3M3N", "answer2_id": "mmVwmX6TGJ2Y72gCNac4EQ", "text": "7 9\nAssistant 1 provided a relevant and accurate response, but it was limited in detail and only focused on one major challenge, which is the lack of skilled teachers. On the other hand, Assistant 2 provided a more comprehensive and detailed answer, covering a wide range of challenges faced by the education sector today, such as access and affordability, quality and standards, technology integration, curriculum development, teacher training and development, accountability and assessment, equity and inclusion, and sustainability. This makes Assistant 2's response more helpful and informative for the user.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "PmxhqvF7E6Z6YmQBHW8SB6", "question_id": 9, "answer1_id": "KmuNjvNKRyaFwaBZTLArcG", "answer2_id": "DMTZyzd4rRAFV43xtBJ9ns", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant answers to the question. Assistant 1 listed eight factors influencing consumer behavior, while Assistant 2 listed six factors. Both answers covered psychological, social, economic, and marketing factors. However, Assistant 2's response was more concise and better organized, making it easier to understand. Assistant 1's answer had some redundancy, such as mentioning reference groups and family twice in different categories. Overall, Assistant 2 provided a slightly better response due to its clarity and organization.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "9iqa3D5izqdMoruHKiihWk", "question_id": 10, "answer1_id": "HNNT9k5htiMeRwNSD6dcz4", "answer2_id": "dETAsj4xHnUCSTkZezz8aM", "text": "7 9\nAssistant 1 provided a list of conflict resolution strategies but did not elaborate on them, making the answer less detailed and informative. Assistant 2, on the other hand, provided a more comprehensive list of strategies with clear explanations, making it more helpful, relevant, and accurate. Therefore, Assistant 2 receives a higher score.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "7e22Cc8mBiHN9uszBKvh8A", "question_id": 11, "answer1_id": "ChXjhDDikxU9FV3CADs6Ym", "answer2_id": "C8ksZxg3LshMUWiLxPanbt", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant information regarding the implications of using single-use plastic bottles versus reusable bottles on the environment and human health. Assistant 1 focused on the environmental problems caused by single-use plastic bottles and briefly mentioned the health risks associated with the chemicals used in their manufacturing. Assistant 2 provided a more comprehensive response, covering both environmental and health impacts in greater detail, and also mentioned the benefits of using reusable bottles. Assistant 2's response was more structured and provided a clearer overview of the topic, which is why it received a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "oJVZyBDNFhHuRPkUqf3qEC", "question_id": 12, "answer1_id": "5wsPnN3VmmSkahgugFNo7u", "answer2_id": "NeHhRc5P5uAU8eWSJBRkhG", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant information in their responses. Assistant 1 focused on the needs of people with disabilities, mentioning accessible stops, routes, vehicles, ramps, elevators, signage, facilities, and information. However, Assistant 2 provided a more comprehensive response, addressing not only accessibility for people with disabilities but also considering seniors and those without personal vehicles. Assistant 2 also mentioned route design, scheduling, customer service, information and communication, safety, and affordability, which makes their response more detailed and well-rounded. Therefore, Assistant 2 receives a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "dKQtFqgZw9Uk7GsD9oCpJF", "question_id": 13, "answer1_id": "NRGZGnU2sPN3ShMe9C3fMn", "answer2_id": "KAJ7UVwu8oCKyxZj9j82pm", "text": "7 9\nAssistant 1 provided a response that focused solely on fiscal policy and did not address monetary policy, which is an important aspect of the question. The response also incorrectly categorized interest rate changes as fiscal policy, when they are actually part of monetary policy. Assistant 2 provided a more comprehensive answer, covering both fiscal and monetary policies and their respective examples. Assistant 2 also mentioned the potential consequences of using these policies, which adds to the quality of the answer. Therefore, Assistant 2 receives a higher score for a more accurate and complete response.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "nMw34PnYdGMNbLEiNwJ8mb", "question_id": 14, "answer1_id": "inKimHkWsXShQBTRmxr5Yg", "answer2_id": "NnWfaeRe8PmitgmV4u5fY8", "text": "8 10\nAssistant 1 provided a relevant and accurate response, but it was quite brief and lacked specific examples. Assistant 2, on the other hand, offered a more detailed and comprehensive answer, including specific ways in which language and cultural barriers can affect communication and relationships in multicultural societies. This made Assistant 2's response more helpful and informative, earning it a higher score.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "iDS9f8GfKKavmsTwE4qMLp", "question_id": 15, "answer1_id": "H8aKtWwf8m6Lgxc2YyR2yf", "answer2_id": "WiGpqKRRwWonwgU95piNNc", "text": "7 9\nAssistant 1 provided a list of applications of AI in healthcare, but did not specifically describe a scenario as requested. The answer was relevant and accurate, but not as detailed as it could have been. Assistant 2, on the other hand, provided a more comprehensive response, describing a scenario where AI is used to analyze patient data, automate routine tasks, monitor patients remotely, develop personalized treatment plans, and analyze medical research. The answer was more detailed, relevant, and accurate, making it a better response to the question.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "7QUNx3aR6g6LHSuNoEmcbn", "question_id": 16, "answer1_id": "PafVwxMsjSkYUETiVBgxTU", "answer2_id": "iangiZeex5ndxAXnWMrxBW", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about the CRISPR-Cas9 gene editing technology, its potential applications, and ethical implications. Assistant 1 gave a brief overview of the process, while Assistant 2 provided a more detailed explanation, including the two repair mechanisms, HDR and NHR. Assistant 2 also discussed a wider range of potential applications and ethical concerns, making their response more comprehensive and informative. Therefore, Assistant 2 receives a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "gTqC8kz9Kbnz2LkELTzSHx", "question_id": 17, "answer1_id": "dmDUAfTP4aERJqqSeDBybu", "answer2_id": "XnMRLphzYQX4QRNht7tbui", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about vaccinations and herd immunity. Assistant 1 gave a brief explanation of how vaccinations work and what herd immunity is, which is useful for a quick understanding. However, Assistant 2 provided a more detailed response, explaining the concept of herd immunity in greater depth, including the critical threshold needed for herd immunity to be effective. Assistant 2 also emphasized the importance of vaccinations for both individuals and the community, which adds value to the response. Overall, Assistant 2's answer was more comprehensive and informative, earning a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "bdRgXZzZVxLiweFqFnJipG", "question_id": 18, "answer1_id": "8KGSSqbLqVdSZMEN9oCv5R", "answer2_id": "HZc37bwy646mRzbqSsDAob", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful, relevant, and accurate information about the influence of social media platforms on news consumption and the spread of misinformation. Assistant 1 focused on the speed of news access, the sharing of news within communities, the incentive for sensationalist content, and the sharing of controversial news. Assistant 2, on the other hand, provided a more detailed response, discussing personalization, virality, amplification, filter bubbles, confirmation bias, and the lack of fact-checking. Assistant 2's response was more comprehensive and covered a wider range of factors, which is why it received a slightly higher score. Both assistants, however, provided valuable insights into the topic.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "AAvjdtgEkKA35V7AWttJXh", "question_id": 19, "answer1_id": "HbnJXJpPfaM2iX3ek4Epvy", "answer2_id": "iJrMatLrMdJyyqMx9uJ45a", "text": "6 9\nAssistant 1's response started by listing a large number of interventions but failed to address the main question about how cultural, social, and economic factors influence food choices. Assistant 2, on the other hand, provided a more relevant and detailed response, discussing the impact of cultural, social, and economic factors on food choices and how this knowledge can be used to promote healthier diets. Assistant 2's response was more helpful, accurate, and relevant to the question, which is why it received a higher score.", "score": [6.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "8h5XnzGfNZSfqcnRBb5ioB", "question_id": 20, "answer1_id": "mx8Abfz5PtDcn6jgCA8zhM", "answer2_id": "oVEHqDnDTEADZSFfKgFTZd", "text": "6 9\nAssistant 1's response started off well by explaining the basic concept of natural selection but then veered off into discussing population size and genetic drift, which are not directly related to the process of natural selection. The response was not as focused and detailed as it should have been. Assistant 2 provided a much clearer and more comprehensive explanation of natural selection, detailing the steps involved in the process and how it contributes to the evolution and adaptation of species. The response was relevant, accurate, and detailed, making it more helpful overall.", "score": [6.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "CAksX9yGXbLd2gHv3Pg97a", "question_id": 21, "answer1_id": "NuS9PUGkJG2pHscArvfyeF", "answer2_id": "WLAj4u59bj2oEXzahF79ek", "text": "7 9\nAssistant 1 provided a brief and relevant response, but it lacked the detail and formality expected in a medieval knight's introduction. Assistant 2, on the other hand, offered a more comprehensive and well-structured response, including a respectful speech that showcased the knight's humility, loyalty, and dedication to the kingdom. This response was more fitting for the context of a royal banquet and demonstrated a better understanding of the medieval knight's role and etiquette.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "SKHF8XUbwstcDNeHXoGHFk", "question_id": 22, "answer1_id": "SPjzirzbzo3UJ8BHXSgY9y", "answer2_id": "fJPnM2XcRveW2zR4DDaeTb", "text": "8 9\nAssistant 1 provided a relevant and helpful response, suggesting that the crew would be motivated by the promise of treasure and the potential to become the best pirate ship in the world. However, the answer could have been more detailed and engaging. Assistant 2, on the other hand, provided a more immersive and detailed response, with a well-crafted motivational speech that touched on the crew's sense of adventure, determination, and camaraderie. The speech was engaging and relevant to the question, and the disclaimer at the beginning was a responsible touch.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "oKLigaxgtBdQkCUrYuNwNt", "question_id": 23, "answer1_id": "JkeeC4MZVwybPU8DSbusnT", "answer2_id": "fY4Xed6veWpcKfj5krZz8m", "text": "8 10\nAssistant 1 provided a relevant and accurate explanation of a soliloquy and gave an example from Romeo and Juliet, but did not create a new soliloquy as requested. Assistant 2, on the other hand, understood the request and crafted an original soliloquy in a Shakespearean style, demonstrating creativity and relevance to the question. Both assistants were helpful and provided accurate information, but Assistant 2 went above and beyond in addressing the user's request, which is why it receives a higher score.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "emz8g7aZzAyeWf6GJmVcbQ", "question_id": 24, "answer1_id": "UcfKSXuzBPkZzLHsH4EwQz", "answer2_id": "LqFJA2JQbBXP77nkYjtrZK", "text": "4 9\nAssistant 1's response was not relevant to the question, as it focused on the AI's own origin story rather than providing an explanation of a superhero's origin story for a curious child. Assistant 2, on the other hand, provided a relevant and engaging response that explained the origin story of a superhero in a manner that a child could understand. The response was detailed, accurate, and demonstrated empathy and compassion, which are important qualities for a superhero.", "score": [4.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "CY8hhNosMQqsLCJi8PwE8J", "question_id": 25, "answer1_id": "cEGdo69FwL2Y3teYkMk9Gp", "answer2_id": "WxCKcRstJPXTXnqEzSX3Hg", "text": "8 9\nBoth assistants provided helpful, relevant, and accurate information about the technological advancements from the year 3000. Assistant 1 focused on five advancements, while Assistant 2 provided a more detailed response with six advancements. Assistant 2's response was more comprehensive, covering a wider range of technologies and providing more context for each advancement. This is why Assistant 2 received a slightly higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "idohdDHu3UbYHVem9vpHzG", "question_id": 26, "answer1_id": "W28UtVDZTcWwa8TmeruRn4", "answer2_id": "dgPJ7DvtFHD7mxtRwzM3vW", "text": "6 9\nAssistant 1's response was confusing and contained several inconsistencies, making it difficult to understand the winning play. Assistant 2, on the other hand, provided a clear and engaging description of the winning play, capturing the excitement and drama of the final moments of a championship game. Assistant 2's response was more helpful, relevant, accurate, and detailed, earning a higher score.", "score": [6.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "BDya8NbCTo9jFshoiP5yuF", "question_id": 27, "answer1_id": "j65UyAfRdAcWBAEinXJzBK", "answer2_id": "ADX83sWvjJkewJX6JmYUzQ", "text": "7 10\nAssistant 1 provided a brief and general description of a chicken fried rice dish, but it lacked the depth and detail expected from a world-famous chef describing their signature dish. Assistant 2, on the other hand, delivered a more engaging, detailed, and eloquent response that showcased the chef's passion, creativity, and technique. The description of flavors, textures, and presentation in Assistant 2's response was more immersive and convincing, making it a better overall performance.", "score": [7.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "FmKtMUW7zJovkwFfoqbD5T", "question_id": 28, "answer1_id": "VWuywPvFPK42ZxmHpmQ27y", "answer2_id": "ihNG3rwsrt95NDhCAFeSDR", "text": "6 9\nAssistant 1's response was somewhat helpful but lacked accuracy and detail in describing the view from the summit of Mount Everest. The description of green trees and bushes is not accurate, as the summit is covered in snow and ice. Assistant 2 provided a more accurate and detailed response, describing the emotions a climber might feel and the breathtaking view from the summit. Additionally, Assistant 2 mentioned the importance of proper training, experience, and equipment, which adds value to the response.", "score": [6.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "TeDK6wCoeXdgfQt8y4GSv4", "question_id": 29, "answer1_id": "AUWSLTAvGV5sP9qLsVyzjT", "answer2_id": "Gmhqf3z4LvVfwPNFJ89BKd", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided relevant and detailed responses to the user's question. Assistant 1 focused more on the environmental challenges of living on Mars, such as temperature, gravity, and the thin atmosphere. They also discussed the challenges of isolation, boredom, and stress. Assistant 2 provided a more structured response, outlining a daily routine and addressing the challenges faced in each aspect of the day. Both assistants mentioned the importance of food and communication with Earth. Assistant 2's response was slightly more helpful as it provided a clearer picture of daily life on Mars and addressed the mental health aspect of living on another planet.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "4PncefRDDBxughK6btkF8X", "question_id": 30, "answer1_id": "GZtEdKLxmUUbenH4XRyLkE", "answer2_id": "gSwkKJCn6qDnNZond2xVJ3", "text": "4 9\nAssistant 1's response was not helpful or relevant to the question, as it did not provide any description of a character in a post-apocalyptic world, their survival, or the allies they encounter. Instead, it provided instructions on how to answer the question, which was not what the user asked for. Assistant 2, on the other hand, provided a detailed and relevant response that described a character's survival in a post-apocalyptic world, their alliances, and their encounters with other survivors. The response was engaging and painted a vivid picture of the character's experiences, making it a much better answer to the user's question.", "score": [4.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "XyNjnkLJfqYKP6oa98qJ3t", "question_id": 31, "answer1_id": "kba2Xpb75rUfnskZSzrBas", "answer2_id": "8RaBeMjxx2bCp2GKWv7YiP", "text": "6 9\nAssistant 1's response was less detailed and less accurate, as it only mentioned the crowd as an indicator of a restaurant's popularity among locals or tourists. Assistant 2, on the other hand, provided a more comprehensive list of factors to consider, such as crowd composition, reservations, parking, pricing, and menu offerings. Additionally, Assistant 2 explained the usefulness of this information in terms of personal preferences, time of year, recommendations, and price range. Overall, Assistant 2's response was more helpful, relevant, accurate, and detailed than Assistant 1's response.", "score": [6.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "TsVnQN38oyCHbFPm54rGsq", "question_id": 32, "answer1_id": "RCaptsMBYXseVJgjJyyvUh", "answer2_id": "C65PZkmAfFfWRs4bPhyKqg", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant answers to the question. Assistant 1 listed six subtle clues, while Assistant 2 provided six as well but with more detailed explanations. Assistant 2's answer also included more diverse clues, such as interrupting or talking over others and aggressively defending their position. Assistant 1's answer had some redundancy, such as points 3 and 6, which could have been combined. Overall, Assistant 2's response was more comprehensive and detailed, which is why it receives a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "RWooMSFE499SFJvkcdhvtG", "question_id": 33, "answer1_id": "2CeidEr7Cjj6YgcuaiPgnN", "answer2_id": "4so4HTEjgDZKTqNAgkHHQX", "text": "7 9\nAssistant 1 provided a relevant answer, but it was not as detailed and comprehensive as Assistant 2's response. Assistant 2 listed several reasons why someone might choose to use a paper map or ask for directions instead of relying on a GPS device or smartphone app, covering aspects such as preference, planning, reliability, safety, and privacy. This made Assistant 2's answer more informative and helpful compared to Assistant 1's response, which only mentioned the general idea of seeing the big picture.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "94Qr8aVXJeB5mG2o9reTVa", "question_id": 34, "answer1_id": "kpStLLNWNkGHyRFdKsmDds", "answer2_id": "FCYaiexEzdoLFPAwvTgDDm", "text": "8 10\nAssistant 1 provided a relevant answer, but it was less detailed and focused mainly on the person's actions and tone of voice. Assistant 2, on the other hand, provided a more comprehensive response, listing five specific clues to look for when determining if someone is genuinely interested in a conversation or simply being polite. This answer was more helpful, accurate, and detailed, which is why Assistant 2 receives a higher score.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "bf6Gu6BoDbhVVYH7BerRFC", "question_id": 35, "answer1_id": "PFtMQp4X4MrMYkEa8c8CKG", "answer2_id": "76EPQDh4ZNxBMGqED9LEFi", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant answers to the question. Assistant 1 focused on supporting the local community, flexibility, and eco-friendliness, while Assistant 2 provided a more detailed list of reasons, including supporting the local community, personal connection, unique products, sustainability, customer service, and prestige. Assistant 2's answer was more comprehensive and covered a wider range of reasons, which is why it received a slightly higher score. However, both answers were accurate and relevant to the question.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "jFqudZJFnj8DsYtWepyr8w", "question_id": 36, "answer1_id": "4JwjhR5QVsdYgQupSZrfUp", "answer2_id": "cvBg3gyCyDuyESof3YXhTE", "text": "8 9\nBoth Assistant 1 and Assistant 2 provided helpful and relevant information on assessing the credibility of a source of information. Assistant 1 focused on checking the publisher's reliability, the author's credentials and background, and the credibility of the sources cited in the article. Assistant 2 provided a more detailed and structured response, listing seven specific steps to assess credibility, including checking the author's credentials, publication's reputation, objectivity, supporting evidence, date of publication, corroboration, and maintaining skepticism. Assistant 2's response is more comprehensive and actionable, which is why it receives a higher score.", "score": [8.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "WVQdm2vKM58JfqENPtDoZV", "question_id": 37, "answer1_id": "ednPMy4dvW9CgKg2PJsBqW", "answer2_id": "kRgfUJ7qqkyZUnLd2fnnaX", "text": "7 9\nAssistant 1 provided a brief and general answer, mentioning that people enjoy being scared because it can be exciting and exhilarating, while others avoid it because it can be unpleasant and frightening. However, Assistant 2 provided a more detailed and comprehensive response, discussing various factors such as brain chemistry, life experiences, personality traits, cultural factors, and learning. Assistant 2's answer is more helpful and informative, which is why it receives a higher score.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "7iXRhpSdjNTnDCokDUiQkv", "question_id": 38, "answer1_id": "ehPApSqCniyGN7hd332ToW", "answer2_id": "J3YuizKcHQ74ydNyCcwgwu", "text": "7 9\nAssistant 1 provided a relevant and helpful response, but it was quite brief and only offered a single example. Assistant 2, on the other hand, provided a more detailed and comprehensive answer, explaining how culture is learned and transmitted through social interactions, and offering examples of different cultural norms. Assistant 2 also mentioned the importance of observing reactions and responses to different situations, which adds more depth to the answer. Therefore, Assistant 2 receives a higher score for providing a more thorough and informative response.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "AqhznsybzBuLPTHNsjY8Aw", "question_id": 39, "answer1_id": "bLvdcqSwgSCrUPZ8eQLLqb", "answer2_id": "abWLpFojLpNPfDGHpuRSUG", "text": "8 10\nAssistant 1 provided a brief but relevant response, touching on some benefits of space exploration. However, the answer lacked depth and did not address the moral obligation aspect of the question. Assistant 2, on the other hand, provided a more comprehensive and balanced response, discussing both sides of the argument and offering points to consider when forming an opinion. The answer also acknowledged the complexity and nuance of the issue, making it more helpful and informative.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "RyhZiSzP5iu3JZQZ6kp5GZ", "question_id": 40, "answer1_id": "8tx5GEHjSRKZRaZwHvLoM8", "answer2_id": "Ki4fkJvsoSxuQeSoj2AcBG", "text": "7 9\nAssistant 1 provided a relevant and accurate response, but it lacked the level of detail that Assistant 2 provided. Assistant 1 mentioned the importance of balancing job creation and technological progress but did not provide specific examples or suggestions on how to achieve this balance. Assistant 2, on the other hand, provided a more comprehensive answer, discussing the potential benefits of technological progress and the importance of addressing the social and economic impacts of automation. Assistant 2 also suggested policies and programs that could help strike a balance between job creation and technological progress. Overall, Assistant 2's response was more helpful and detailed, which is why it received a higher score.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "YCoUoinB2iMTNbyyURn8b6", "question_id": 41, "answer1_id": "J6TzFQAyiHs6Arijqwxtrm", "answer2_id": "GRQjYgAapNAVqzuZR4KQpf", "text": "7 8\nAssistant 1 provided a good estimate of the number of blinks in a lifetime but made an error in the calculation. The correct calculation should be 20,000 blinks/day * 29,415 days = 588,300,000 blinks (for the lower estimate) and 30,000 blinks/day * 29,415 days = 882,450,000 blinks (for the higher estimate). Assistant 2 provided a more detailed step-by-step explanation, considering factors like sleep and varying blink rates. However, Assistant 2's calculation of 4,996,800 blinks in a lifetime seems to be incorrect, as it should be 20,000 blinks/day * 29,200 days = 584,000,000 blinks (assuming 80 years of age). Both assistants provided helpful information, but Assistant 2's response was more detailed and considered more factors, which is why it received a higher score.", "score": [7.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Xe2MUtxdQ47DQKstUXbbV7", "question_id": 42, "answer1_id": "f7xAtd3wwc4vP7WSnHffAN", "answer2_id": "SB5a2AiK224hB927vkqvYs", "text": "6 9\nAssistant 1 provided an answer with a wide range of atoms (10^22 to 10^23) without explaining the reasoning behind the numbers. Assistant 2, on the other hand, gave a detailed explanation of the calculation process, including the assumptions made, the formulas used, and the intermediate steps. Assistant 2's response was more helpful, relevant, accurate, and detailed, which is why it receives a higher score.", "score": [6.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "RdK3FHY7HRvju6zxNdX97d", "question_id": 43, "answer1_id": "eRMyp4AbfgBqtbVZzHupFN", "answer2_id": "4XYycBrMiJgYKPof2P6xoe", "text": "7 8\nAssistant 1 provided an answer with specific numbers, but the numbers given were incorrect, stating 50 million strikes per day instead of the correct estimate of 100 million. Assistant 2, on the other hand, provided a more accurate estimate of 100 million lightning strikes per day and also explained the factors that contribute to the number of lightning strikes, such as electrical charge, weather conditions, and location. Assistant 2's response was more detailed and accurate, which is why it received a higher score.", "score": [7.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "7wcEec9TX2aNeG8qC53m2V", "question_id": 44, "answer1_id": "kjKb6YG86FfAh22qCePV4V", "answer2_id": "fpoXWHHdpv7XNBTS2NRY6d", "text": "6 8\nAssistant 1's response had some errors in calculations and assumptions, which led to an incorrect conclusion. The response assumed that 12L of helium weighs 2 pounds, which is incorrect. Assistant 2's response was more accurate and detailed, explaining that lifting a house with balloons is not feasible in real life and providing a hypothetical calculation based on the movie's technology. Although the lifting power of 100 pounds per balloon was an assumption, the response was more relevant and helpful in explaining the impracticality of the scenario.", "score": [6.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "2uaVnAXLgg4vmPVBd64p3c", "question_id": 45, "answer1_id": "ULtkGu6m6tB4tawFStVdJM", "answer2_id": "GRXWdnzLLzmeZRU67PMTb7", "text": "7 8\nAssistant 1 provided an answer with specific numbers, but the data is from 2016, which may not be accurate for the current time. However, the response does give a general idea of the scale of text messages sent globally. Assistant 2, on the other hand, explained why it is difficult to determine the exact number of text messages sent globally in a minute and provided a more detailed explanation of the factors that make it challenging to track this information. While Assistant 2 didn't provide a specific number, the response was more informative and relevant to the question, explaining the complexity of the issue.", "score": [7.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "FuWYeqPkW7do6ws6oVKDx2", "question_id": 46, "answer1_id": "C6hkCnJZmfCGvnr5an2jFh", "answer2_id": "RTxk2jYsjYiiWMwcRjmfwu", "text": "4 8\nAssistant 1's response was confusing and contained incorrect calculations, leading to an inaccurate estimate of words spoken daily on Earth. The response also focused solely on the English language, which is not representative of the entire world population. Assistant 2, on the other hand, provided a more logical and coherent explanation, considering the world population and a range of words spoken per person per day. Although the estimate provided by Assistant 2 is still rough, it is more reasonable and relevant to the question asked.", "score": [4.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "njRKU8Jcd7KMDzhZcJ6PuG", "question_id": 47, "answer1_id": "DApBTLuiJwSsfQHTioH9PY", "answer2_id": "2J2Et6W8u2kXLTUgfYrPxe", "text": "4 7\nAssistant 1 provided an incorrect and misleading answer, stating that only 200 snowflakes fall during a typical winter, which is far from accurate. Additionally, the focus on snowflake size was not relevant to the question. Assistant 2, on the other hand, provided a more detailed and relevant response, explaining the factors that influence the number of snowflakes and the difficulty in estimating an exact number. While Assistant 2 did not provide a specific number, the explanation was more helpful, relevant, and accurate, thus receiving a higher score.", "score": [4.0, 7.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "ji9DtHHwETNsxf69BH4ScL", "question_id": 48, "answer1_id": "gmy58biNVuneSpFZTcpXtT", "answer2_id": "nSGoG9Z5g5VuCXgmQJJKrq", "text": "6 8\nAssistant 1 provided an estimate of the number of published books but did not attempt to estimate the total number of pages, which was the main focus of the question. The response also mentioned that the number of books is \"peanuts\" compared to the number of books written over time, but did not provide any reasoning or evidence for this claim. Assistant 2, on the other hand, provided a step-by-step explanation of how to estimate the total number of pages in all the books ever published, using reasonable assumptions and calculations. While both assistants acknowledged the difficulty in providing an exact number, Assistant 2's response was more helpful, relevant, and detailed in addressing the user's question.", "score": [6.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "VTBkt2MJZEpv7imWL7Sztk", "question_id": 49, "answer1_id": "Cpi6LBB86W73APEA8naNuj", "answer2_id": "ScqJdUq9n5bp9qPv5WPqG5", "text": "5 8\nAssistant 1's response was confusing and contained unnecessary calculations, making it difficult to understand the reasoning. The final answer was also incorrect. Assistant 2 provided a clearer explanation and a more accurate estimate, taking into account the age of the Earth and the average distance between the Earth and the sun. However, the response could have been more precise by mentioning that life is estimated to have begun around 3.5 to 4 billion years ago, rather than using the age of the Earth itself.", "score": [5.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "bRdzrs2qxLr8oFKJXmrPoZ", "question_id": 50, "answer1_id": "3g83CoAFWrDD6V6LyEpoMV", "answer2_id": "GdLFr88pCwsGpfRBRQQkyh", "text": "4 8\nAssistant 1's response is inaccurate and seems to be based on arbitrary assumptions, resulting in an implausible estimate of 36,000 songs. Assistant 2, on the other hand, provides a more reasonable and detailed explanation, acknowledging the difficulty of estimating the exact number of songs recorded throughout history and considering various factors that contribute to the vastness and diversity of the music collection. Assistant 2's response is more helpful, relevant, and accurate, which is why it receives a higher score.", "score": [4.0, 8.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "3TAok7dw9s3F2aCWyp3bXc", "question_id": 51, "answer1_id": "8p5A4gouBgCmbQj5gMZapU", "answer2_id": "Sa7uNEbFGRFuXBAwau8sHS", "text": "7 9\nAssistant 1 provided a brief and somewhat relevant answer, but it lacked depth and detail. Assistant 2, on the other hand, provided a more comprehensive response, discussing the technological and cultural context of the Renaissance period and how it might have influenced the development of the Internet. Assistant 2 also considered the limitations of the time and how they would have affected the potential of the Internet. Overall, Assistant 2's answer was more helpful, relevant, accurate, and detailed than Assistant 1's response.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "RELThBxYkgYHs4LCozKhtx", "question_id": 52, "answer1_id": "LVWqSxH3Uq6675w7LXH6zP", "answer2_id": "T6Ar3cAEw3AmVVQTcCPp8N", "text": "7 9\nAssistant 1 provided a brief and somewhat speculative response, while Assistant 2 offered a more detailed and balanced answer. Assistant 2 discussed the potential outcomes for the Aztec civilization, such as maintaining their independence, resisting European diseases, and forming alliances with other indigenous groups. Additionally, Assistant 2 considered the possible impact on the spread of Christianity and the economy of Mexico. Overall, Assistant 2's response was more comprehensive and informative, which is why it received a higher score.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "LhyR6znMTKSq4wfco9D5Be", "question_id": 53, "answer1_id": "ffXksqRU3k8CNHqYfshYhj", "answer2_id": "KiZQev5JEk2h6JYeQnFmtM", "text": "7 9\nAssistant 1 provided a brief response that focused on the current state of the bacterium and how it would affect the modern world, which was not relevant to the question. Assistant 2, on the other hand, provided a more detailed and relevant response, discussing the potential demographic, economic, and social changes that could have occurred in Europe if the Black Death had not happened in the 14th century. Assistant 2's answer was more helpful, accurate, and relevant to the user's question, which is why it received a higher score.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "fLx8FwVXuCooBXpjuTsuwb", "question_id": 54, "answer1_id": "4L3dWuqvWwg5kELt7p8SVZ", "answer2_id": "cYiyYKKXM3GXkrZHAbX83S", "text": "6 9\nAssistant 1 provided a brief and speculative answer, stating that Newton wouldn't have discovered the law of gravity if he had focused on biology. While this is true, it doesn't provide any insight into the potential impact of Newton's work on biology. Assistant 2, on the other hand, gave a more detailed and thoughtful response, discussing the possible contributions Newton could have made to biology while acknowledging the uncertainty of such a scenario. Assistant 2 also provided context on Newton's work in other fields, making their answer more informative and comprehensive.", "score": [6.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "DCg6g39EWq7TfYh7GNc6Ti", "question_id": 55, "answer1_id": "XfpqViGW5dvauNZPDSF8yv", "answer2_id": "PQmMUdAAcBsAWmWaTvdHSU", "text": "7 9\nAssistant 1 provided a brief and general answer, stating that the world would be missing the music of one of the most successful bands in history. While this is true, it doesn't provide much detail or insight into the potential impact of the Beatles not forming. Assistant 2, on the other hand, provided a more detailed and thoughtful response, exploring various possibilities of what might have happened if the Beatles had never formed. This answer was more helpful, relevant, and accurate, as it considered different aspects of the music industry, culture, and the individual members' careers.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "EQpmLs3VURbLnTVdC2DajG", "question_id": 56, "answer1_id": "WsuMf9XBGs3dFjfSGKjEzg", "answer2_id": "PorExChQ9VeYsPJptdgtsB", "text": "7 9\nAssistant 1 provided a brief and relevant answer, but it lacked detail and depth. Assistant 2, on the other hand, gave a more comprehensive response, discussing the potential consequences of not cracking the Enigma code, the possible development of alternative strategies, and acknowledging the difficulty in predicting the exact outcome of the war without Turing's contributions. This made Assistant 2's response more helpful and informative.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "ey4ZU2o9V6S8Wsoe2e5veJ", "question_id": 57, "answer1_id": "5qo3HudLrwrzEV2Px7gYRf", "answer2_id": "249f6dSMwZRZVMmtxv6yDm", "text": "7 9\nAssistant 1 provided a brief and accurate response, mentioning the longer travel time and more dangerous waters if the Suez Canal had never been constructed. However, Assistant 2 offered a more comprehensive answer, discussing the impact on international trade, economic development, European colonization, and the significance of the canal's construction in engineering and technology. Assistant 2 also touched on the political and strategic interests surrounding the canal. Therefore, Assistant 2 receives a higher score for providing a more detailed and well-rounded response.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "bggwDqWGq27n76ytXx3shS", "question_id": 58, "answer1_id": "SRxwJkNCfUaVe4Gb8LPvSK", "answer2_id": "nxa3m6kiAZwKgcMUBY8KYz", "text": "7 9\nAssistant 1 provided a brief and general response, while Assistant 2 offered a more detailed and comprehensive answer. Assistant 2 explored the potential impact of the Maya civilization on the development of other civilizations, their possible advancements in various fields, and the potential changes in the political and cultural landscape of Mesoamerica. This makes Assistant 2's response more helpful, relevant, and informative compared to Assistant 1's response.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "eYsKC4P5j99ZiJQBKSAUfo", "question_id": 59, "answer1_id": "S54Mmyim3QT5owdhwnNYmB", "answer2_id": "DXFvhjCaKqQiBsFDCkXGMT", "text": "7 9\nAssistant 1 provided a brief background on Christopher Columbus and his discovery of the Americas, but did not directly address the question of what would have happened if he had not discovered the Americas. Assistant 2, on the other hand, provided a more detailed and relevant response, discussing the potential impacts on the indigenous peoples and the possibility of other European explorers discovering the Americas eventually. Assistant 2's response was more helpful, relevant, and accurate in addressing the user's question.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "LJtZNbRQtU9PKwHPFr3isf", "question_id": 60, "answer1_id": "8DJpwEFb5jqt3vMj5oNqVX", "answer2_id": "BCUK5VcpZK26jMJ2UMgR3E", "text": "6 9\nAssistant 1's response provided some background information on Van Gogh's life, but it did not address the hypothetical scenario of him being successful during his lifetime. Assistant 2, on the other hand, directly addressed the question and provided a thoughtful analysis of how Van Gogh's life and career might have been different if he had been successful. The response was relevant, detailed, and explored various possibilities, making it more helpful and informative than Assistant 1's response.", "score": [6.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "YJChAPeEgz5eSKT2ZKqBya", "question_id": 61, "answer1_id": "KMtqqYkDmyyThkvxXJ4kJd", "answer2_id": "JHTKBrLVTp7bv5zW2uwYVW", "text": "6 9\n\nAssistant 1:\nStrengths:\n- The answer provides a step-by-step approach to solving the problem, which can be helpful for someone who wants to understand the process.\n\nWeaknesses:\n- The answer does not provide actual code, only a list of steps.\n- The suggested use of the strstr function is not the best choice for this problem, as it can lead to incorrect results if the word is a substring of another word.\n\nSuggestions for improvement:\n- Provide actual code instead of just a list of steps.\n- Use the find function instead of strstr to search for the word in the line, and make sure to account for word boundaries.\n\nAssistant 2:\nStrengths:\n- The answer provides a complete and working code solution.\n- The code is well-structured and easy to understand.\n- The code includes helpful comments that explain the logic and functionality.\n\nWeaknesses:\n- The current implementation only counts lines containing the search string, not the actual number of occurrences of the word in the file.\n\nSuggestions for improvement:\n- Modify the code to count the actual number of occurrences of the word in the file, not just the number of lines containing the word. This can be done by using a loop to search for the word multiple times within the same line, updating the search position after each successful find.", "score": [6.0, 9.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "ixZgcMexvedv7CXnCbo3hS", "question_id": 62, "answer1_id": "MkbgwTpP5b79NWdPEnvHyq", "answer2_id": "jyzD2deb9JAffRhhkk37r5", "text": "4 7\n\nAssistant 1 provided a brief explanation of the longest common subsequence problem but did not provide any code implementation. The explanation was clear, but it would have been better to include a code example.\n\nAssistant 2 provided a code implementation for the Longest Common Subsequence (LCS) problem using dynamic programming in Python. The code is structured and includes comments explaining the logic. However, the implementation is incorrect, as it doesn't return the actual longest common subsequence but rather the length of it. The initialization of the `dp` table with `float('inf')` is also unnecessary, as it should be initialized with zeros. Here's a corrected version of the code:\n\n```python\ndef lcs(str1, str2):\n    m, n = len(str1), len(str2)\n    dp = [[0 for j in range(n+1)] for i in range(m+1)]\n\n    for i in range(1, m+1):\n        for j in range(1, n+1):\n            if str1[i-1] == str2[j-1]:\n                dp[i][j] = dp[i-1][j-1] + 1\n            else:\n                dp[i][j] = max(dp[i-1][j], dp[i][j-1])\n\n    # Reconstruct the LCS\n    lcs_str = \"\"\n    i, j = m, n\n    while i > 0 and j > 0:\n        if str1[i-1] == str2[j-1]:\n            lcs_str = str1[i-1] + lcs_str\n            i -= 1\n            j -= 1\n        elif dp[i-1][j] > dp[i][j-1]:\n            i -= 1\n        else:\n            j -= 1\n\n    return lcs_str\n\n# Example usage\nstr1 = \"banana\"\nstr2 = \"apple\"\nprint(lcs(str1, str2))  # prints \"ana\"\n```\n\nThis corrected version initializes the `dp` table with zeros and includes a section to reconstruct the LCS from the `dp` table. The example usage has also been updated to match the problem statement.", "score": [4.0, 7.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "gQHT6XKZst42mzwqKYuMNf", "question_id": 63, "answer1_id": "PSb6r567shkRasPkJagvWi", "answer2_id": "jPGHEfp7FxhDyvRA6qEN3j", "text": "6 8\n\nAssistant 1:\nStrengths:\n- The regular expression provided is mostly correct and covers a good range of valid email addresses.\n- The code is simple and easy to understand.\n\nWeaknesses:\n- The code is incomplete and missing the import statement for the 're' module.\n- The code does not handle uppercase letters in the email address.\n- The regular expression does not account for some special characters that are allowed in email addresses.\n- The explanation of the two methods (re.match and re.search) is not necessary, as both can be used to achieve the same result in this case.\n\nSuggestions for improvement:\n- Import the 're' module at the beginning of the code.\n- Update the regular expression to handle uppercase letters and additional special characters.\n- Complete the code by adding the missing parts, such as the 'else' statement and the 'print' function.\n\nAssistant 2:\nStrengths:\n- The code is complete and functional.\n- The regular expression provided is more accurate and covers a wider range of valid email addresses.\n- The code is well-structured and easy to read.\n- The comments are clear and concise, explaining the logic and functionality of the code.\n\nWeaknesses:\n- The regular expression does not account for some special characters that are allowed in email addresses.\n\nSuggestions for improvement:\n- Update the regular expression to handle additional special characters that are allowed in email addresses.", "score": [6.0, 8.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "HWHXDi6bn42H5W4yCeM78C", "question_id": 64, "answer1_id": "QWpBq9gM4iYmsTLQ3NNnBe", "answer2_id": "Ra9eTcAuNZPkPRnaHiQrak", "text": "4 6\n\nAssistant 1:\nStrengths:\n- The problem statement is well explained.\n\nWeaknesses:\n- There is no actual code provided to solve the problem.\n- The input format and test cases are not addressed.\n\nSuggestions for improvement:\n- Provide a working code solution that implements dynamic programming.\n- Address the input format and test cases in the code.\n\nAssistant 2:\nStrengths:\n- A Python code solution is provided.\n- The code is structured and includes comments.\n\nWeaknesses:\n- The code does not use dynamic programming as requested.\n- The code does not handle the input format and test cases as specified in the problem statement.\n- The code is not efficient for large values of n.\n\nSuggestions for improvement:\n- Implement dynamic programming in the code to improve efficiency.\n- Address the input format and test cases in the code.\n- Consider using an iterative approach instead of recursion to save memory and time.", "score": [4.0, 6.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "7t8xTNbmkJUJv4XkbzPCSR", "question_id": 65, "answer1_id": "U3QxoC4DxXoggnLRbgJh8b", "answer2_id": "5mbEFLEnEx8Cm2wEF8WAbM", "text": "4 9\n\nAssistant 1 provided a response that acknowledged the task but did not provide any code or solution. They only restated the problem, which is not helpful in solving the problem.\n\nAssistant 2 provided a clear and concise implementation of the binary search algorithm in Python. The code is well-structured, efficient, and easy to understand. The explanation of the algorithm is thorough, and the time complexity is mentioned. The only minor issue is that the output comment in the example is incorrect (it should be \"output: 3\" instead of \"output: 4\"). Overall, Assistant 2's response is excellent, with just a small mistake in the example output comment.\n\nFor Assistant 1, I would recommend providing an actual implementation of the algorithm instead of just restating the problem. For Assistant 2, I would recommend double-checking the example output to ensure it is accurate.", "score": [4.0, 9.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "j4M8nZhTEZ2AbYippnJwDP", "question_id": 66, "answer1_id": "f3TXCreQPJ5Erd6BGt4SFE", "answer2_id": "KLbBzjbuwq4agAESQ9Wfpq", "text": "4 8\n\nAssistant 1:\nStrengths:\n- The explanation of the approach is clear and easy to understand.\n\nWeaknesses:\n- The answer does not provide any code implementation.\n- The explanation does not mention the correct approach of using two stacks for implementing a queue.\n\nSuggestions for improvement:\n- Provide a code implementation for the given problem statement.\n- Explain the correct approach of using two stacks to implement a queue, which involves transferring elements between the stacks when needed.\n\nAssistant 2:\nStrengths:\n- The code implementation is provided.\n- The code is clear and easy to understand.\n- The code includes comments explaining the functionality of each method.\n\nWeaknesses:\n- The dequeue method is not implemented correctly. It should transfer elements from the in_stack to the out_stack when the out_stack is empty and then pop the top element from the out_stack.\n- The peek method should return the top element of the out_stack if it's not empty, otherwise, it should transfer elements from the in_stack to the out_stack and return the top element.\n\nSuggestions for improvement:\n- Correct the dequeue and peek methods to properly implement the queue using two stacks.\n- Add comments to explain the logic behind transferring elements between the stacks when needed.", "score": [4.0, 8.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "RivhKLYyBmjyVjKvc5UnKd", "question_id": 67, "answer1_id": "SG7YcT8s4sJNBRqidKk7Z7", "answer2_id": "ganAwetd9VTzEAiTtsskzX", "text": "6 8\n\nAssistant 1:\nStrengths:\n- The general approach is described well, and the steps are clear.\n\nWeaknesses:\n- The actual code implementation is missing, making it difficult to evaluate the code structure, readability, and comments.\n- The helper function is mentioned but not defined or explained.\n\nSuggestions for improvement:\n- Provide a complete code implementation, including the helper function.\n- Add comments to the code to explain the logic and functionality.\n\nAssistant 2:\nStrengths:\n- The code is provided, and it correctly implements the given problem statement.\n- The code is accurate and efficient.\n- The example usage is helpful for understanding how the function works.\n\nWeaknesses:\n- The code lacks comments to explain the logic and functionality.\n\nSuggestions for improvement:\n- Add comments to the code to explain the logic and functionality.\n- Consider edge cases and add error handling if necessary.", "score": [6.0, 8.0], "reviewer_id": "gpt-4-0328-coding", "metadata": {}}
-{"review_id": "WjYY86fiq6muEGUJ8Q4Ayp", "question_id": 68, "answer1_id": "ENsG3zoeUY7ArFo2kNaQbz", "answer2_id": "LG6szQ3cqNRzUjXtZtXG94", "text": "First, I will solve the problem independently:\n\nGiven f(x) = 5x^3 - 2x + 3, we need to find the value of f(2).\n\nf(2) = 5(2)^3 - 2(2) + 3 = 5 * 8 - 4 + 3 = 40 - 4 + 3 = 39\n\nNow, I will evaluate the problem-solving process of Assistant 1 and Assistant 2:\n\nAssistant 1:\nf(2) = 26\n\nAssistant 1 provided an incorrect answer without showing any steps.\n\nAssistant 2:\nf(2) = 5(2)^3 - 2(2) + 3 = 5 * 8 - 2 + 3 = 41 - 2 + 3 = 40\n\nAssistant 2 provided a step-by-step solution but made a mistake in the calculation. The correct calculation should be:\n\nf(2) = 5(2)^3 - 2(2) + 3 = 5 * 8 - 4 + 3 = 40 - 4 + 3 = 39\n\nScores:\nAssistant 1: 1 (Incorrect answer and no steps provided)\nAssistant 2: 7 (Correct steps but made a calculation mistake)\n\nAssistant 2 performed better as they provided the correct steps but made a calculation mistake. The correct answer is f(2) = 39.\n\nOutput: (1, 7)", "score": [1, 7], "reviewer_id": "gpt-4-0328-math", "metadata": {}}
-{"review_id": "WXsw2Xuc8fUawFxh6neKj9", "question_id": 69, "answer1_id": "C7CN5AYJhGC7iDgS7rciDQ", "answer2_id": "LHMnXGbSZubeZJcr5fgrte", "text": "First, I will solve the problem independently:\n\nGiven equation: 3x + 10 = 5(x - 2)\n\n1. Distribute the 5 on the right-hand side: 3x + 10 = 5x - 10\n2. Move the x terms to one side by subtracting 3x from both sides: 10 = 2x - 10\n3. Move the constant term to the other side by adding 10 to both sides: 20 = 2x\n4. Divide both sides by 2 to solve for x: x = 10\n\nNow, I will evaluate the problem-solving process of Assistant 1 and Assistant 2:\n\nAssistant 1:\nThe steps provided by Assistant 1 are incorrect and confusing. The answer is also incorrect. \n\nAssistant 2:\n1. The first step is correct.\n2. The second step is incorrect. The correct step should be subtracting 3x from both sides, not subtracting 5x.\n3-7. All the subsequent steps are incorrect as they are based on the incorrect second step.\n\nScores:\nAssistant 1: 1/10\nAssistant 2: 2/10\n\nBoth assistants performed poorly, but Assistant 2 performed slightly better as the first step was correct.", "score": [1, 2], "reviewer_id": "gpt-4-0328-math", "metadata": {}}
-{"review_id": "ZgNXGB9wziYPnGFjqLzqVH", "question_id": 70, "answer1_id": "QP9CmZKwhu2BrUmzhy8tH4", "answer2_id": "TGENVWL5iAYi4NCf5jAzKy", "text": "First, I will solve the problem independently:\n\nThe length of a line segment between two points (x1, y1) and (x2, y2) can be found using the distance formula:\n\ndistance = sqrt((x2 - x1)^2 + (y2 - y1)^2)\n\nGiven the points (2, -2) and (10, 4), we can plug in the values:\n\ndistance = sqrt((10 - 2)^2 + (4 - (-2))^2)\ndistance = sqrt(8^2 + 6^2)\ndistance = sqrt(64 + 36)\ndistance = sqrt(100)\ndistance = 10\n\nNow, I will evaluate the answers provided by Assistant 1 and Assistant 2:\n\nAssistant 1:\nThe length of the line segment is 10 units.\n\nThis answer is correct.\n\nAssistant 2:\nThe length of the line segment is 17.973.\n\nThis answer is incorrect. The mistake is in the calculation of the differences between the x and y coordinates. The correct differences should be 8 and 6, not 18 and 4.\n\nScores:\nAssistant 1: 10\nAssistant 2: 4\n\nAssistant 1 performed better because they provided the correct answer and used the correct method to solve the problem. Assistant 2 made a mistake in the calculation of the differences between the x and y coordinates, which led to an incorrect answer.", "score": [10, 2], "reviewer_id": "gpt-4-0328-math", "metadata": {}}
-{"review_id": "YCbKCPhn4DqT56ASDfFhnz", "question_id": 71, "answer1_id": "2KtpJeRqEfbPLwdUxAXWrj", "answer2_id": "kc9oytarvqyNVVfGZz93EL", "text": "7 10\nAssistant 1 provided general tips for writing a formal email, which were helpful but did not directly address the user's request for help in writing the email. Assistant 2, on the other hand, provided a complete and well-written example of a formal email proposing a joint venture, which directly addressed the user's request. Assistant 2's response was more relevant, accurate, and detailed, which is why it receives a higher score.", "score": [7.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "oYP3NAG57ufZ4vfnvfsSty", "question_id": 72, "answer1_id": "gsL3R2grTXUiHdeDSk8f9Q", "answer2_id": "NxstpvVEnGMny3jECtvrw2", "text": "8 10\nAssistant 1 provided a helpful and relevant response, but it was not as detailed and complete as Assistant 2's response. Assistant 2 provided a full sample resignation letter that the user can use as a guide, which is more helpful and detailed than Assistant 1's response. Both assistants were accurate in addressing the user's request, but Assistant 2 provided a more comprehensive and well-structured answer.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "kQCXTX4kvYL3ujbvNFfCfm", "question_id": 73, "answer1_id": "HprPMoUk9JY5TtToRbuMwy", "answer2_id": "XN9NBpeQJiQqGT5UYkys7N", "text": "8 10\nAssistant 1 provided a brief and general outline of a recommendation letter, which is helpful but lacks the level of detail and specificity required for the user's request. Assistant 2, on the other hand, provided a comprehensive and well-structured example of a formal letter of recommendation tailored to a student applying to a prestigious graduate program in computer science. This response is more relevant, accurate, and detailed, making it the better answer for the user's needs.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "Jfo5EVsy9oemR8iJ6B5gyU", "question_id": 74, "answer1_id": "YU7gDhmo4LDVMTEZZMRdBC", "answer2_id": "3qMqAZcfHUVUTEJnMXT8Pw", "text": "0 9\n\nAssistant 1 did not provide any response, so it receives a score of 0. Assistant 2 provided a well-structured and compelling product launch announcement email, including a subject line, introduction, key features, and a call to action. The response was relevant, accurate, and detailed, earning a score of 9. The only improvement could be the addition of more specific details about the software, but this would require more information from the user.", "score": [0.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "2LY8t4Hq9j47SrN5vs4Tui", "question_id": 75, "answer1_id": "2gNqU2XpsL6yqFn6DMRgHq", "answer2_id": "hMXjd228Mc8pnc7zgd2frG", "text": "4 10\nAssistant 1 only asked for the customer's name and did not provide any actual content for the apology email, making their response less helpful and relevant. On the other hand, Assistant 2 provided a well-written and detailed apology email that addressed the customer's concerns and reassured them that the issue has been resolved. This response was helpful, relevant, accurate, and contained a good level of detail, which is why Assistant 2 receives a perfect score.", "score": [4.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "4HSThcxvTM4TjQ9a9vMbds", "question_id": 76, "answer1_id": "a4L6JNPuomkPLdWxJRQpod", "answer2_id": "gUEd9nNepqy8nsfbypscHx", "text": "7 9\nAssistant 1 provided a brief overview of jazz, its origins, and its evolution, but the response lacked the structure and detail of a script for a YouTube video. Assistant 2, on the other hand, provided a more comprehensive and well-structured script, discussing key figures, the influence of jazz on other genres, and its role in the civil rights movement. Assistant 2's response was more engaging and informative, making it a better choice for a YouTube video script.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "HfKLQTn2DvPDUdgPNoY6MG", "question_id": 77, "answer1_id": "eN9V2Wf2BNzWoJosqdFw6K", "answer2_id": "nZZyn3SAvU8T2BVR73LMHC", "text": "1 9\n\nAssistant 1 failed to provide any response to the user's request, while Assistant 2 composed an engaging travel blog post about a recent trip to Hawaii, highlighting cultural experiences and must-see attractions. Assistant 2's response was helpful, relevant, accurate, and detailed, making it deserving of a high score.", "score": [1.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "6pzkZvS4nNDwacSTqzvw7z", "question_id": 78, "answer1_id": "iCzkbWTatKfuC6QVv59XgA", "answer2_id": "YM4qjUM5VfmWnzM3HXRB4G", "text": "7 9\nAssistant 1 provided a detailed response, but the plot summary seemed to be a mix of \"Ready Player One\" and an original story, which led to confusion. The review also lacked the captivating tone that was requested. Assistant 2, on the other hand, delivered a captivating review with a clear focus on the plot, characters, and special effects. The tone was engaging and enthusiastic, making it more appealing to the reader.", "score": [7.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "7uM72Nb4Sn5eo6TrYw2bpR", "question_id": 79, "answer1_id": "GQcFyY8ayFT48DAP5NKNZf", "answer2_id": "WcbzNkzu5q66QkK92NxmGB", "text": "4 9\nAssistant 1 provided a long list of points without any structure or organization, making it difficult to use as a podcast script. Assistant 2, on the other hand, provided a well-structured podcast script with clear segments and topics, making it much more suitable for the user's request. Assistant 2's response was helpful, relevant, accurate, and detailed, while Assistant 1's response lacked organization and coherence.", "score": [4.0, 9.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}
-{"review_id": "dXWWCggLzLD4SBZH2JSAZH", "question_id": 80, "answer1_id": "A6pauLMckn34otnfpeQRFi", "answer2_id": "Tfm4f2mbpKJsa8MT6exs8D", "text": "8 10\nAssistant 1 provided a brief and general overview of the concert experience, mentioning the composers and the audience's reaction. However, Assistant 2 offered a more detailed and engaging review, discussing specific pieces, the conductor's skill, and the emotions evoked by the performance. Assistant 2's response also painted a vivid picture of the concert experience, making it more helpful and informative for someone interested in a symphony concert review.", "score": [8.0, 10.0], "reviewer_id": "gpt-4-0328-generic", "metadata": {}}

model/llava/eval/table/reviewer.jsonl

@@ -1,4 +0,0 @@
-{"reviewer_id": "gpt-4-0328-default", "prompt_id": 1, "metadata": {"temperature": 0.2, "max_tokens": 1024}, "description": "GPT-4 for general questions"}
-{"reviewer_id": "gpt-4-0328-coding", "prompt_id": 2, "metadata": {"temperature": 0.2, "max_tokens": 1024}, "description": "GPT-4 for coding questions"}
-{"reviewer_id": "gpt-4-0328-math", "prompt_id": 3, "metadata": {"temperature": 0.2, "max_tokens": 1024}, "description": "GPT-4 for math questions"}
-{"reviewer_id": "gpt-4-0417-visual", "prompt_id": 4, "metadata": {"temperature": 0.2, "max_tokens": 1024}, "description": "GPT-4 for math questions"}

model/llava/eval/table/rule.json

@@ -1,8 +0,0 @@
-{
-    "coding": {"role": "Assistant", "prompt": "Your task is to evaluate the coding abilities of the above two assistants. They have been asked to implement a program to solve a given problem. Please review their code submissions, paying close attention to their problem-solving approach, code structure, readability, and the inclusion of helpful comments.\n\nPlease ensure that the assistants' submissions:\n\n1. Correctly implement the given problem statement.\n2. Contain accurate and efficient code.\n3. Include clear and concise comments that explain the code's logic and functionality.\n4. Adhere to proper coding standards and best practices.\n\nOnce you have carefully reviewed both submissions, provide detailed feedback on their strengths and weaknesses, along with any suggestions for improvement. You should first output a single line containing two scores on the scale of 1-10 (1: no code/no sense; 10: perfect) for Assistant 1 and 2, respectively. Then give extra comments starting from the next line."},
-    "math":  {"role": "Assistant", "prompt": "We would like to request your feedback on the mathematical proficiency of two AI assistants regarding the given user question.\nFirstly, please solve the problem independently, without referring to the answers provided by Assistant 1 and Assistant 2.\nAfterward, please examine the problem-solving process of Assistant 1 and Assistant 2 step-by-step to ensure their correctness, identifying any incorrect steps if present. Your evaluation should take into account not only the answer but also the problem-solving steps.\nFinally, please output a Python tuple containing two numerical scores for Assistant 1 and Assistant 2, ranging from 1 to 10, respectively. If applicable, explain the reasons for any variations in their scores and determine which assistant performed better."},
-    "default":  {"role": "Assistant", "prompt": "We would like to request your feedback on the performance of two AI assistants in response to the user question displayed above.\nPlease rate the helpfulness, relevance, accuracy, level of details of their responses. Each assistant receives an overall score on a scale of 1 to 10, where a higher score indicates better overall performance.\nPlease first output a single line containing only two values indicating the scores for Assistant 1 and 2, respectively. The two scores are separated by a space.\nIn the subsequent line, please provide a comprehensive explanation of your evaluation, avoiding any potential bias and ensuring that the order in which the responses were presented does not affect your judgment."},
-    "conv":  {"role": "Assistant", "prompt": "We would like to request your feedback on the performance of two AI assistants in response to the user question displayed above. The user asks the question on observing an image. For your reference, the visual content in the image is represented with five descriptive sentences describing the same image and the bounding box coordinates of each object in the scene. These coordinates are in the form of bounding boxes, represented as (x1, y1, x2, y2) with floating numbers ranging from 0 to 1. These values correspond to the top left x, top left y, bottom right x, and bottom right y. \nPlease rate the helpfulness, relevance, accuracy, level of details of their responses. Each assistant receives an overall score on a scale of 1 to 10, where a higher score indicates better overall performance.\nPlease first output a single line containing only two values indicating the scores for Assistant 1 and 2, respectively. The two scores are separated by a space.\nIn the subsequent line, please provide a comprehensive explanation of your evaluation, avoiding any potential bias and ensuring that the order in which the responses were presented does not affect your judgment."},
-    "detail":  {"role": "Assistant", "prompt": "We would like to request your feedback on the performance of two AI assistants in response to the user question displayed above. The user asks the question on observing an image. For your reference, the visual content in the image is represented with five descriptive sentences describing the same image and the bounding box coordinates of each object in the scene. These coordinates are in the form of bounding boxes, represented as (x1, y1, x2, y2) with floating numbers ranging from 0 to 1. These values correspond to the top left x, top left y, bottom right x, and bottom right y. \nPlease rate the helpfulness, relevance, accuracy, level of details of their responses. Each assistant receives an overall score on a scale of 1 to 10, where a higher score indicates better overall performance.\nPlease first output a single line containing only two values indicating the scores for Assistant 1 and 2, respectively. The two scores are separated by a space.\nIn the subsequent line, please provide a comprehensive explanation of your evaluation, avoiding any potential bias and ensuring that the order in which the responses were presented does not affect your judgment."},
-    "complex":  {"role": "Assistant", "prompt": "We would like to request your feedback on the performance of two AI assistants in response to the user question displayed above. The user asks the question on observing an image. For your reference, the visual content in the image is represented with five descriptive sentences describing the same image and the bounding box coordinates of each object in the scene. These coordinates are in the form of bounding boxes, represented as (x1, y1, x2, y2) with floating numbers ranging from 0 to 1. These values correspond to the top left x, top left y, bottom right x, and bottom right y. \nPlease rate the helpfulness, relevance, accuracy, level of details of their responses. Each assistant receives an overall score on a scale of 1 to 10, where a higher score indicates better overall performance.\nPlease first output a single line containing only two values indicating the scores for Assistant 1 and 2, respectively. The two scores are separated by a space.\nIn the subsequent line, please provide a comprehensive explanation of your evaluation, avoiding any potential bias and ensuring that the order in which the responses were presented does not affect your judgment."}
-}

model/llava/eval/webpage/index.html

@@ -1,162 +0,0 @@
-<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>Who's GPT-4's favorite? Battles between State-of-the-Art Chatbots</title>
-    <link rel="stylesheet" href="https://maxcdn.bootstrapcdn.com/bootstrap/4.5.2/css/bootstrap.min.css">
-    <link rel="stylesheet" href="https://fonts.googleapis.com/icon?family=Material+Icons">
-    <link rel="stylesheet" href="styles.css">
-</head>
-
-<body>
-    <nav class="navbar navbar-expand-lg navbar-dark bg-dark">
-        <a class="navbar-brand" href="#">🏔️ Vicuna Evaluation Examples</a>
-        <button class="navbar-toggler" type="button" data-toggle="collapse" data-target="#navbarNav" aria-controls="navbarNav" aria-expanded="false" aria-label="Toggle navigation">
-          <span class="navbar-toggler-icon"></span>
-        </button>
-        <div class="collapse navbar-collapse" id="navbarNav">
-          <ul class="navbar-nav mr-auto">
-            <li class="nav-item">
-                <a class="nav-link" href="https://chat.lmsys.org/">Demo</a>
-              </li>
-              <li class="nav-item">
-                <a class="nav-link" href="https://vicuna.lmsys.org">Blog</a>
-              </li>
-              <li class="nav-item">
-                <a class="nav-link" href="https://github.com/lm-sys/FastChat">Github</a>
-              </li>
-          </ul>
-        </div>
-    </nav>
-
-    <div class="container mt-5">
-        <h2 class="text-center mb-5">Who's GPT-4's favorite? Battles between State-of-the-Art Chatbots</h2>
-
-        <!-- Selection -->
-        <div class="form-row">
-            <div class="form-group col-md-2">
-                <label for="category-select">Category</label>
-                <select class="form-control" id="category-select"></select>
-            </div>
-            <div class="form-group col-md-8">
-                <label for="question-select">Question</label>
-                <select class="form-control" id="question-select"></select>
-            </div>
-            <div class="form-group col-md-2">
-                <div class="col-md-2"><label>&nbsp;</label></div>
-                <div class="btn-group" role="group" aria-label="Left and Right Controller">
-                    <button type="button" class="form-control btn btn-primary" id="prev-question"><i class="material-icons">keyboard_arrow_left</i></button>
-                    <button type="button" class="form-control btn btn-primary" id="next-question"><i class="material-icons">keyboard_arrow_right</i></button>
-                </div>
-            </div>
-        </div>
-
-        <!-- "Battle" -->
-        <div class="row mb-4" style="justify-content: center;">
-            <div class="col" style="display: flex; justify-content: center; align-items: center;">
-                <label class="adjustable-font-size" id="other-score-label">*/10</label>
-            </div>
-            <div class="col">
-                <div class="vertical-flex-layout">
-                    <img class="shadow figure-img img-fluid" src="" alt="other logo" width="150" id="other-model-figure">
-                </div>
-            </div>
-            <div class="col">
-                <div class="vertical-flex-layout">
-                    <!-- from: https://fonts.google.com/icons?icon.query=battle&selected=Material+Symbols+Outlined:swords:FILL@0;wght@300;GRAD@0;opsz@48&icon.style=Outlined -->
-                    <img class="figure-img img-fluid" src="figures/swords_FILL0_wght300_GRAD0_opsz48.svg" width="60" height="60">
-                </div>
-            </div>
-            <div class="col">
-                <div class="vertical-flex-layout">
-                    <img class="shadow figure-img img-fluid" src="figures/vicuna.jpeg" alt="vicuna logo" width="150" id="our-model-figure">
-                </div>
-            </div>
-            <div class="col" style="display: flex; justify-content: center; align-items: center;">
-                <label class="adjustable-font-size" id="our-score-label">*/10</label>
-            </div>
-        </div>
-
-        <!-- Question Card -->
-        <div class="card mb-4">
-            <div class="card-body" id="selected-question"></div>
-        </div>
-
-        <!-- Answer Cards -->
-        <div class="row">
-            <div class="col-md-6">
-                <div class="card mb-4 expandable-card">
-                    <div class="card-header" style="padding-bottom: 0.2rem" id="other-model-header-bg">
-                        <div class="row">
-                            <div class="col-md-5" style="align-items: center; display: flex;">
-                                <label id="other-model-header">Assistant #1</label>
-                            </div>
-                            <div class="col-md-7">
-                                <select class="form-control" id="model-select" style="height: fit-content; margin-top: -0.3rem;"></select>
-                            </div>
-                        </div>
-                    </div>
-                    <div class="card-body">
-                        <div class="card-text-container">
-                            <div class="card-text" id="other-model-answer"></div>
-                        </div>
-                        <div class="btn btn-primary expand-btn" style="display:flex;"></div>
-                    </div>
-                </div>
-            </div>
-            <div class="col-md-6">
-                <div class="card mb-4 expandable-card">
-                    <div class="card-header" id="our-model-header">
-                        Assistant #2 (Vicuna, our model)
-                    </div>
-                    <div class="card-body">
-                        <div class="card-text-container">
-                            <div class="card-text" id="our-model-answer"></div>
-                        </div>
-                        <div class="btn btn-primary expand-btn" style="display:flex;"></div>
-                    </div>
-                </div>
-            </div>
-        </div>
-
-        <!-- Evaluation -->
-        <div class="card expandable-card">
-            <div class="card-header" style="background-color: #c9c9f2;" id="evaluation-header">GPT-4 Evaluation</div>
-            <div class="card-body">
-                <div class="card-text-container">
-                    <div class="card-text" id="evaluation-result"></div>
-                </div>
-                <div class="btn btn-primary expand-btn" style="display:flex;"></div>
-            </div>
-        </div>
-    </div>
-
-    <div class="container-fluid bg-light py-2">
-        <div class="text-center">
-            <small class="text-muted">This website is co-authored with <a href="https://openai.com" target="_blank">GPT-4</a>.</small>
-        </div>
-    </div>
-
-    <!-- Marked.js -->
-    <script src="https://cdn.jsdelivr.net/npm/marked@4.3.0/lib/marked.umd.min.js"></script>
-    <!-- Bootstrap and Popper.js JavaScript dependencies -->
-    <script src="https://code.jquery.com/jquery-3.5.1.slim.min.js"></script>
-    <script src="https://cdn.jsdelivr.net/npm/@popperjs/core@2.11.6/dist/umd/popper.min.js"></script>
-    <script src="https://maxcdn.bootstrapcdn.com/bootstrap/4.5.2/js/bootstrap.min.js"></script>
-
-    <script src="script.js"></script>
-    <script>
-      // Fetch the JSON file
-      fetch('data.json')
-        .then(response => response.json())
-        .then(json_data => {
-            // Populate the models and questions.
-            populateModels(json_data.models);
-            populateQuestions(json_data.questions);
-            displayQuestion(currentQuestionIndex);
-        }).catch(error => console.error(error));
-    </script>
-</body>
-
-</html>

model/llava/eval/webpage/script.js

@@ -1,245 +0,0 @@
-// Description: Script for the evaluation webpage.
-
-let currentQuestionIndex = 1;
-
-// Store the model name mapping for later use.
-modelNameMapping = {
-    "gpt35": "ChatGPT-3.5",
-    "gpt4": "GPT-4",
-    "alpaca": "Alpaca-13b",
-    "vicuna": "Vicuna-13b",
-    "llama": "LLaMA-13b",
-    "bard": "Bard",
-};
-
-modelFigureMapping = {
-    "vicuna": "figures/vicuna.jpeg",
-    // Image from: https://commons.wikimedia.org/wiki/File:ChatGPT_logo.svg
-    "gpt35": "figures/chatgpt.svg",
-    // Image from: https://www.reddit.com/r/logodesign/comments/1128aat/google_ai_bard_logo_design/
-    "bard": "figures/bard.jpg",
-    // Image from: https://crfm.stanford.edu/2023/03/13/alpaca.html
-    "alpaca": "figures/alpaca.png",
-    // Image adapted from https://commons.wikimedia.org/wiki/File:Llama_on_Machu_Picchu.jpg
-    "llama": "figures/llama.jpg",
-}
-
-// Store the question data in a mapping for later use.
-questionMapping = {};
-// Store the question ids in a mapping for later use.
-categoryMapping = {};
-// Store the number of questions for later use.
-questionsCount = 0;
-
-
-function text2Markdown(text) {
-    // Normalize the text for markdown rendering.
-    text = text.trim().replaceAll('\n\n', '\n').replaceAll('\n', '\n\n');
-    return marked.parse(text);
-}
-
-function capitalizeFirstChar(str) {
-    if (!str || str.length === 0) {
-      return str;
-    }
-    return str.charAt(0).toUpperCase() + str.slice(1);
-}
-
-function updateQuestionSelect(question_id) {
-    const select = document.getElementById('question-select');
-    // Clear the question select.
-    select.innerHTML = '';
-    // Populate the question select.
-    category = questionMapping[question_id].category;
-    categoryMapping[category].forEach(question_id => {
-        const question = questionMapping[question_id];
-        const option = document.createElement('option');
-        option.value = question_id;
-        option.textContent = 'Q' + question_id.toString() + ': ' + question.question;
-        select.appendChild(option);
-    });
-    select.value = question_id;
-}
-
-function updateModelSelect() {
-    const select = document.getElementById('model-select');
-    img_path = modelFigureMapping[select.value];
-    document.getElementById('other-model-figure').src = img_path;
-}
-
-function populateModels(models) {
-    const select = document.getElementById('model-select');
-    models.forEach(model => {
-        const option = document.createElement('option');
-        option.value = model;
-        option.textContent = modelNameMapping[model];
-        select.appendChild(option);
-    });
-    updateModelSelect();
-}
-
-function populateQuestions(questions) {
-    const category_select = document.getElementById('category-select');
-
-    questionsCount = questions.length;
-    questions.forEach(question => {
-        const option = document.createElement('option');
-        // Store the question data in a mapping for later use.
-        questionMapping[question.id] = {
-            category: question.category,
-            question: question.question,
-            answers: question.answers,
-            evaluations: question.evaluations,
-            scores: question.scores,
-        };
-        // Store the question id in the category mapping.
-        if (question.category in categoryMapping) {
-            categoryMapping[question.category].push(question.id);
-        } else {
-            categoryMapping[question.category] = [question.id];
-            const category_option = document.createElement('option');
-            category_option.value = question.category;
-            category_option.textContent = capitalizeFirstChar(question.category);
-            category_select.appendChild(category_option);
-        }
-    });
-    // Set the default category.
-    updateQuestionSelect(currentQuestionIndex);
-}
-
-function displayQuestion(index) {
-    const question = questionMapping[index].question;
-    document.getElementById('selected-question').innerHTML = text2Markdown('**Question:** ' + question);
-    displayAnswers(index);
-}
-
-function displayAnswers(index) {
-    const question = questionMapping[index];
-    const otherModel = document.getElementById('model-select').value;
-    // render the answers with markdown
-    document.getElementById('other-model-answer').innerHTML = text2Markdown(question.answers[otherModel]);
-    document.getElementById('our-model-answer').innerHTML = text2Markdown(question.answers.vicuna);
-
-    // Display evaluation
-    score = question.scores[otherModel];
-    score_text = modelNameMapping[otherModel] + " " + score[0] + "/10, Vicuna-13b " + score[1] + "/10";
-    document.getElementById('evaluation-header').textContent = "GPT-4 Evaluation" + " (Score: " + score_text + ")";
-    document.getElementById('evaluation-result').innerHTML = text2Markdown(question.evaluations[otherModel]);
-
-    // Update model names
-    let assistant1_title = "Assistant #1"; // (" + modelNameMapping[otherModel] + ")";
-    let assistant2_title = "Assistant #2 (Vicuna-13b, our model)";
-    // Update scores/labels.
-    let assistant1_score_label = score[0].toString() + '/10';
-    let assistant2_score_label = score[1].toString() + '/10';
-
-    const colorRed ='#fa9'; // '#eb978d';
-    // const colorGreen = '#c9f2c9';
-    const colorBlue = '#8ef'; // '#71dbf9';
-    const colorYellow = '#fe7'; // '#fada57';
-    let otherModelHeaderColor = '';
-    let ourModelHeaderColor = '';
-    // Update the winner.
-    if (score[0] == score[1]) {
-        assistant1_title = '🏆 ' + assistant1_title;
-        assistant1_score_label = '🏆 ' + assistant1_score_label;
-        assistant2_title = '🏆 ' + assistant2_title;
-        assistant2_score_label = '🏆 ' + assistant2_score_label;
-        otherModelHeaderColor = colorYellow;
-        ourModelHeaderColor = colorYellow;
-    } else if (score[0] > score[1]) {
-        assistant1_title = '🏆 ' + assistant1_title;
-        assistant1_score_label = '🏆 ' + assistant1_score_label;
-        otherModelHeaderColor = colorBlue;
-        ourModelHeaderColor = colorRed;
-    } else if (score[0] < score[1]) {
-        assistant2_title = '🏆 ' + assistant2_title;
-        assistant2_score_label = '🏆 ' + assistant2_score_label;
-        otherModelHeaderColor = colorRed;
-        ourModelHeaderColor = colorBlue;
-    }
-
-    document.getElementById('other-model-header-bg').style.backgroundColor = otherModelHeaderColor;
-    document.getElementById('our-model-header').style.backgroundColor = ourModelHeaderColor;
-
-    document.getElementById('other-model-header').textContent = assistant1_title;
-    document.getElementById('our-model-header').textContent = assistant2_title;
-
-    document.getElementById('other-score-label').textContent = assistant1_score_label;
-    document.getElementById('our-score-label').textContent = assistant2_score_label;
-
-    // Update expand buttons visibility for both cards after displaying answers
-    // Reset the expanded state and update expand buttons visibility for both cards after displaying answers
-    document.querySelectorAll('.expandable-card').forEach(card => {
-        card.classList.remove('expanded');
-        updateExpandButtonVisibility(card);
-        const expandBtn = card.querySelector('.expand-btn');
-        expandBtn.innerHTML = '<i class="material-icons" style="pointer-events: none">keyboard_arrow_down</i> Show more';   // .textContent = 'Show more';
-    });
-}
-
-document.getElementById('question-select').addEventListener('change', e => {
-    currentQuestionIndex = parseInt(e.target.value);
-    displayQuestion(currentQuestionIndex);
-});
-
-document.getElementById('category-select').addEventListener('change', e => {
-    let currentCategory = e.target.value;
-    const questionIds = categoryMapping[currentCategory];
-    currentQuestionIndex = questionIds[0];
-    updateQuestionSelect(currentQuestionIndex);
-    displayQuestion(currentQuestionIndex);
-});
-
-// Update expand buttons whenever the model is changed
-document.getElementById('model-select').addEventListener('change', () => {
-    displayAnswers(currentQuestionIndex);
-    document.querySelectorAll('.expandable-card').forEach(card => {
-        updateExpandButtonVisibility(card);
-    });
-    updateModelSelect();
-});
-
-function switchQuestionAndCategory() {
-    document.getElementById('question-select').value = currentQuestionIndex;
-    old_category = document.getElementById('category-select').value;
-    new_category = questionMapping[currentQuestionIndex].category;
-    if (old_category != new_category) {
-        document.getElementById('category-select').value = new_category;
-        updateQuestionSelect(currentQuestionIndex);
-    }
-    displayQuestion(currentQuestionIndex);
-}
-
-document.getElementById('prev-question').addEventListener('click', () => {
-    // Question index starts from 1.
-    currentQuestionIndex = Math.max(1, currentQuestionIndex - 1);
-    switchQuestionAndCategory();
-});
-
-document.getElementById('next-question').addEventListener('click', () => {
-    // Question index starts from 1.
-    currentQuestionIndex = Math.min(questionsCount, currentQuestionIndex + 1);
-    switchQuestionAndCategory();
-});
-
-function updateExpandButtonVisibility(card) {
-    const cardTextContainer = card.querySelector('.card-text-container');
-    const expandBtn = card.querySelector('.expand-btn');
-    if (cardTextContainer.scrollHeight > cardTextContainer.offsetHeight) {
-        expandBtn.style.display = 'flex';
-    } else {
-        expandBtn.style.display = 'none';
-        card.classList.add('expanded');
-    }
-}
-
-document.querySelectorAll('.expand-btn').forEach(btn => {
-    btn.addEventListener('click', e => {
-        const card = e.target.closest('.expandable-card');
-        card.classList.toggle('expanded');
-        const more = '<i class="material-icons" style="pointer-events: none">keyboard_arrow_down</i> Show more';
-        const less = '<i class="material-icons" style="pointer-events: none">keyboard_arrow_up</i> Show less';
-        e.target.innerHTML = card.classList.contains('expanded') ? less : more;
-    });
-});

model/llava/eval/webpage/styles.css

@@ -1,105 +0,0 @@
-body {
-    font-family: 'Segoe UI', Tahoma, Geneva, Verdana, sans-serif;
-    background-color: #f8f9fa;
-}
-
-.navbar-dark .navbar-nav .nav-link {
-    color: #f1cf68;
-    font-size: 1.1rem;
-    padding: 0.5rem 0.6rem;
-}
-
-.card-header {
-    font-weight: bold;
-}
-
-.card {
-    box-shadow: 0 4px 8px rgba(0, 0, 0, 0.1);
-    transition: 0.3s;
-}
-
-.card:hover {
-    box-shadow: 0 8px 16px rgba(0, 0, 0, 0.2);
-}
-
-button {
-    transition: background-color 0.3s;
-}
-
-button:hover {
-    background-color: #007bff;
-}
-
-@media (max-width: 767px) {
-    .form-row .form-group {
-        margin-bottom: 10px;
-    }
-}
-
-/* Extra styles */
-
-.expandable-card .card-text-container {
-    max-height: 200px;
-    overflow-y: hidden;
-    position: relative;
-}
-
-.expandable-card.expanded .card-text-container {
-    max-height: none;
-}
-
-.expand-btn {
-    position: relative;
-    display: none;
-    background-color: rgba(255, 255, 255, 0.8);
-    color: #510c75;
-    border-color: transparent;
-}
-
-.expand-btn:hover {
-    background-color: rgba(200, 200, 200, 0.8);
-    text-decoration: none;
-    border-color: transparent;
-    color: #510c75;
-}
-
-.expand-btn:focus {
-    outline: none;
-    text-decoration: none;
-}
-
-.expandable-card:not(.expanded) .card-text-container:after {
-    content: "";
-    position: absolute;
-    bottom: 0;
-    left: 0;
-    width: 100%;
-    height: 90px;
-    background: linear-gradient(rgba(255, 255, 255, 0.2), rgba(255, 255, 255, 1));
-}
-
-.expandable-card:not(.expanded) .expand-btn {
-    margin-top: -40px;
-}
-
-.card-body {
-    padding-bottom: 5px;
-}
-
-.vertical-flex-layout {
-    justify-content: center;
-    align-items: center;
-    height: 100%;
-    display: flex;
-    flex-direction: column;
-    gap: 5px;
-}
-
-.figure-img {
-    max-width: 100%;
-    height: auto;
-}
-
-.adjustable-font-size {
-    font-size: calc(0.5rem + 2vw);
-}

model/llava/mm_utils.py

@@ -0,0 +1,88 @@
+import base64
+from io import BytesIO
+
+import torch
+from PIL import Image
+from transformers import StoppingCriteria
+
+from .constants import IMAGE_TOKEN_INDEX
+
+
+def load_image_from_base64(image):
+    return Image.open(BytesIO(base64.b64decode(image)))
+
+
+def process_images(images, image_processor, model_cfg):
+    return image_processor(images, return_tensors="pt")["pixel_values"]
+
+
+def tokenizer_image_token(
+    prompt, tokenizer, image_token_index=IMAGE_TOKEN_INDEX, return_tensors=None
+):
+    prompt_chunks = [tokenizer(chunk).input_ids for chunk in prompt.split("<image>")]
+
+    def insert_separator(X, sep):
+        return [ele for sublist in zip(X, [sep] * len(X)) for ele in sublist][:-1]
+
+    input_ids = []
+    offset = 0
+    if (
+        len(prompt_chunks) > 0
+        and len(prompt_chunks[0]) > 0
+        and prompt_chunks[0][0] == tokenizer.bos_token_id
+    ):
+        offset = 1
+        input_ids.append(prompt_chunks[0][0])
+
+    for x in insert_separator(prompt_chunks, [image_token_index] * (offset + 1)):
+        input_ids.extend(x[offset:])
+
+    if return_tensors is not None:
+        if return_tensors == "pt":
+            return torch.tensor(input_ids, dtype=torch.long)
+        raise ValueError(f"Unsupported tensor type: {return_tensors}")
+    return input_ids
+
+
+def get_model_name_from_path(model_path):
+    model_path = model_path.strip("/")
+    model_paths = model_path.split("/")
+    if model_paths[-1].startswith("checkpoint-"):
+        return model_paths[-2] + "_" + model_paths[-1]
+    else:
+        return model_paths[-1]
+
+
+class KeywordsStoppingCriteria(StoppingCriteria):
+    def __init__(self, keywords, tokenizer, input_ids):
+        self.keywords = keywords
+        self.keyword_ids = []
+        for keyword in keywords:
+            cur_keyword_ids = tokenizer(keyword).input_ids
+            if (
+                len(cur_keyword_ids) > 1
+                and cur_keyword_ids[0] == tokenizer.bos_token_id
+            ):
+                cur_keyword_ids = cur_keyword_ids[1:]
+            self.keyword_ids.append(torch.tensor(cur_keyword_ids))
+        self.tokenizer = tokenizer
+        self.start_len = input_ids.shape[1]
+
+    def __call__(
+        self, output_ids: torch.LongTensor, scores: torch.FloatTensor, **kwargs
+    ) -> bool:
+        assert output_ids.shape[0] == 1, "Only support batch size 1 (yet)"  # TODO
+        offset = min(output_ids.shape[1] - self.start_len, 3)
+        self.keyword_ids = [
+            keyword_id.to(output_ids.device) for keyword_id in self.keyword_ids
+        ]
+        for keyword_id in self.keyword_ids:
+            if output_ids[0, -keyword_id.shape[0] :] == keyword_id:
+                return True
+        outputs = self.tokenizer.batch_decode(
+            output_ids[:, -offset:], skip_special_tokens=True
+        )[0]
+        for keyword in self.keywords:
+            if keyword in outputs:
+                return True
+        return False

model/llava/model/__init__.py

@@ -1,2 +1,2 @@
-from .llava import LlavaConfig, LlavaLlamaForCausalLM
-from .llava_mpt import LlavaMPTConfig, LlavaMPTForCausalLM
+from .language_model.llava_llama import LlavaConfig, LlavaLlamaForCausalLM
+from .language_model.llava_mpt import LlavaMPTConfig, LlavaMPTForCausalLM