updated leaderboard

README.md

@@ -8,7 +8,8 @@ sdk_version: 4.4.0
 app_file: app.py
 pinned: true
 license: apache-2.0
-duplicated_from: HuggingFaceH4/open_llm_leaderboard
 ---
 
 Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+
+Most of the variables to change for a default leaderboard are in env (replace the path for your leaderboard) and src/display/about.

app.py

@@ -3,7 +3,7 @@ import pandas as pd
 from apscheduler.schedulers.background import BackgroundScheduler
 from huggingface_hub import snapshot_download
 
-from src.display.about import (
+from display.about import (
     CITATION_BUTTON_LABEL,
     CITATION_BUTTON_TEXT,
     EVALUATION_QUEUE_TEXT,
@@ -25,13 +25,13 @@ from src.display.utils import (
     WeightType,
     Precision
 )
-from src.envs import API, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, H4_TOKEN, QUEUE_REPO, REPO_ID, RESULTS_REPO
+from src.envs import API, EVAL_REQUESTS_PATH, EVAL_RESULTS_PATH, TOKEN, QUEUE_REPO, REPO_ID, RESULTS_REPO
 from src.populate import get_evaluation_queue_df, get_leaderboard_df
 from src.submission.submit import add_new_eval
 
 
 def restart_space():
-    API.restart_space(repo_id=REPO_ID, token=H4_TOKEN)
+    API.restart_space(repo_id=REPO_ID, token=TOKEN)
 
 try:
     print(EVAL_REQUESTS_PATH)
@@ -91,8 +91,7 @@ def select_columns(df: pd.DataFrame, columns: list) -> pd.DataFrame:
     return filtered_df
 
 
-def filter_queries(query: str, filtered_df: pd.DataFrame):
-    """Added by Abishek"""
+def filter_queries(query: str, filtered_df: pd.DataFrame) -> pd.DataFrame:
     final_df = []
     if query != "":
         queries = [q.strip() for q in query.split(";")]

src/display/about.py

@@ -1,31 +1,33 @@
 from src.display.utils import ModelType
+from enum import Enum
+from dataclasses import dataclass
 
-# To complete, what is your leaderboard name
+@dataclass
+class Task:
+    benchmark: str
+    metric: str
+    col_name: str
+
+# Init: to update with your specific keys
+class Tasks(Enum):
+    task0 = Task("Key in the harness", "metric in the harness", "Display name 1")
+    task1 = Task("Key in the harness", "metric in the harness", "Display name 2")
+
+
+# Your leaderboard name
 TITLE = """<h1 align="center" id="space-title">Leaderboard</h1>"""
 
-# to complete - what does your leaderboard evaluate
+# What does your leaderboard evaluate?
 INTRODUCTION_TEXT = """
 """
 
-# to complete - which evaluations are you running? how can people reproduce what you have?
+# Which evaluations are you running? how can people reproduce what you have?
 LLM_BENCHMARKS_TEXT = f"""
 ## How it works
 
 ## Reproducibility
 To reproduce our results, here is the commands you can run:
 
-## Quantization
-To get more information about quantization, see:
-- 8 bits: [blog post](https://huggingface.co/blog/hf-bitsandbytes-integration), [paper](https://arxiv.org/abs/2208.07339)
-- 4 bits: [blog post](https://huggingface.co/blog/4bit-transformers-bitsandbytes), [paper](https://arxiv.org/abs/2305.14314)
-
-## Model types
-- {ModelType.PT.to_str(" : ")} model: new, base models, trained on a given corpora
-- {ModelType.FT.to_str(" : ")} model: pretrained models finetuned on more data
-Specific fine-tune subcategories (more adapted to chat):
-- {ModelType.IFT.to_str(" : ")} model: instruction fine-tunes, which are model fine-tuned specifically on datasets of task instruction 
-- {ModelType.RL.to_str(" : ")} model: reinforcement fine-tunes, which usually change the model loss a bit with an added policy. 
-If there is no icon, we have not uploaded the information on the model yet, feel free to open an issue with the model information!
 """
 
 EVALUATION_QUEUE_TEXT = """

src/display/utils.py

@@ -3,21 +3,11 @@ from enum import Enum
 
 import pandas as pd
 
+from src.display.about import Tasks
+
 def fields(raw_class):
     return [v for k, v in raw_class.__dict__.items() if k[:2] != "__" and k[-2:] != "__"]
 
-
-@dataclass
-class Task:
-    benchmark: str
-    metric: str
-    col_name: str
-
-# Init: to update with your specific keys
-class Tasks(Enum):
-    task0 = Task("Key in the harness", "metric in the harness", "display name")
-    task1 = Task("Key in the harness", "metric in the harness", "display name")
-
 # These classes are for user facing column names,
 # to avoid having to change them all around the code
 # when a modif is needed
@@ -30,6 +20,7 @@ class ColumnContent:
     never_hidden: bool = False
     dummy: bool = False
 
+## Leaderboard columns
 auto_eval_column_dict = []
 # Init
 auto_eval_column_dict.append(["model_type_symbol", ColumnContent, ColumnContent("T", "str", True, never_hidden=True)])
@@ -54,6 +45,7 @@ auto_eval_column_dict.append(["dummy", ColumnContent, ColumnContent("model_name_
 # We use make dataclass to dynamically fill the scores from Tasks
 AutoEvalColumn = make_dataclass("AutoEvalColumn", auto_eval_column_dict, frozen=True)
 
+## For the queue columns in the submission tab
 @dataclass(frozen=True)
 class EvalQueueColumn:  # Queue column
     model = ColumnContent("model", "markdown", True)
@@ -63,24 +55,7 @@ class EvalQueueColumn:  # Queue column
     weight_type = ColumnContent("weight_type", "str", "Original")
     status = ColumnContent("status", "str", True)
 
-baseline_row = {
-    AutoEvalColumn.model.name: "<p>Baseline</p>",
-    AutoEvalColumn.revision.name: "N/A",
-    AutoEvalColumn.precision.name: None,
-    AutoEvalColumn.average.name: 0,
-    AutoEvalColumn.dummy.name: "baseline",
-    AutoEvalColumn.model_type.name: "",
-}
-
-human_baseline_row = {
-    AutoEvalColumn.model.name: "<p>Human performance</p>",
-    AutoEvalColumn.revision.name: "N/A",
-    AutoEvalColumn.precision.name: None,
-    AutoEvalColumn.average.name: 0,
-    AutoEvalColumn.dummy.name: "human_baseline",
-    AutoEvalColumn.model_type.name: "",
-}
-
+## All the model information that we might need
 @dataclass
 class ModelDetails:
     name: str

src/envs.py

@@ -3,9 +3,9 @@ import os
 from huggingface_hub import HfApi
 
 # clone / pull the lmeh eval data
-H4_TOKEN = os.environ.get("H4_TOKEN", None)
+TOKEN = os.environ.get("TOKEN", None)
 
-OWNER = "clefourrier"
+OWNER = "demo-leaderboard"
 REPO_ID = f"{OWNER}/leaderboard"
 QUEUE_REPO = f"{OWNER}/requests"
 RESULTS_REPO = f"{OWNER}/results"
@@ -16,4 +16,4 @@ CACHE_PATH=os.getenv("HF_HOME", ".")
 EVAL_REQUESTS_PATH = os.path.join(CACHE_PATH, "eval-queue")
 EVAL_RESULTS_PATH = os.path.join(CACHE_PATH, "eval-results")
 
-API = HfApi(token=H4_TOKEN)
+API = HfApi(token=TOKEN)

src/tools/collections.py

@@ -1,83 +0,0 @@
-import os
-
-import pandas as pd
-from huggingface_hub import add_collection_item, delete_collection_item, get_collection, update_collection_item
-from huggingface_hub.utils._errors import HfHubHTTPError
-from pandas import DataFrame
-
-from src.display.utils import AutoEvalColumn, ModelType
-from src.envs import H4_TOKEN, PATH_TO_COLLECTION
-
-# Specific intervals for the collections
-intervals = {
-    "1B": pd.Interval(0, 1.5, closed="right"),
-    "3B": pd.Interval(2.5, 3.5, closed="neither"),
-    "7B": pd.Interval(6, 8, closed="neither"),
-    "13B": pd.Interval(10, 14, closed="neither"),
-    "30B": pd.Interval(25, 35, closed="neither"),
-    "65B": pd.Interval(60, 70, closed="neither"),
-}
-
-
-def update_collections(df: DataFrame):
-    """This function updates the Open LLM Leaderboard model collection with the latest best models for
-    each size category and type.
-    """
-    collection = get_collection(collection_slug=PATH_TO_COLLECTION, token=H4_TOKEN)
-    params_column = pd.to_numeric(df[AutoEvalColumn.params.name], errors="coerce")
-
-    cur_best_models = []
-
-    ix = 0
-    for type in ModelType:
-        if type.value.name == "":
-            continue
-        for size in intervals:
-            # We filter the df to gather the relevant models
-            type_emoji = [t[0] for t in type.value.symbol]
-            filtered_df = df[df[AutoEvalColumn.model_type_symbol.name].isin(type_emoji)]
-
-            numeric_interval = pd.IntervalIndex([intervals[size]])
-            mask = params_column.apply(lambda x: any(numeric_interval.contains(x)))
-            filtered_df = filtered_df.loc[mask]
-
-            best_models = list(
-                filtered_df.sort_values(AutoEvalColumn.average.name, ascending=False)[AutoEvalColumn.dummy.name]
-            )
-            print(type.value.symbol, size, best_models[:10])
-
-            # We add them one by one to the leaderboard
-            for model in best_models:
-                ix += 1
-                cur_len_collection = len(collection.items)
-                try:
-                    collection = add_collection_item(
-                        PATH_TO_COLLECTION,
-                        item_id=model,
-                        item_type="model",
-                        exists_ok=True,
-                        note=f"Best {type.to_str(' ')} model of around {size} on the leaderboard today!",
-                        token=H4_TOKEN,
-                    )
-                    if (
-                        len(collection.items) > cur_len_collection
-                    ):  # we added an item - we make sure its position is correct
-                        item_object_id = collection.items[-1].item_object_id
-                        update_collection_item(
-                            collection_slug=PATH_TO_COLLECTION, item_object_id=item_object_id, position=ix
-                        )
-                        cur_len_collection = len(collection.items)
-                    cur_best_models.append(model)
-                    break
-                except HfHubHTTPError:
-                    continue
-
-    collection = get_collection(PATH_TO_COLLECTION, token=H4_TOKEN)
-    for item in collection.items:
-        if item.item_id not in cur_best_models:
-            try:
-                delete_collection_item(
-                    collection_slug=PATH_TO_COLLECTION, item_object_id=item.item_object_id, token=H4_TOKEN
-                )
-            except HfHubHTTPError:
-                continue

src/tools/model_backlinks.py

@@ -1,1309 +0,0 @@
-models = [
-    "uni-tianyan/Uni-TianYan",
-    "fangloveskari/ORCA_LLaMA_70B_QLoRA",
-    "garage-bAInd/Platypus2-70B-instruct",
-    "upstage/Llama-2-70b-instruct-v2",
-    "fangloveskari/Platypus_QLoRA_LLaMA_70b",
-    "yeontaek/llama-2-70B-ensemble-v5",
-    "TheBloke/Genz-70b-GPTQ",
-    "TheBloke/Platypus2-70B-Instruct-GPTQ",
-    "psmathur/model_007",
-    "yeontaek/llama-2-70B-ensemble-v4",
-    "psmathur/orca_mini_v3_70b",
-    "ehartford/Samantha-1.11-70b",
-    "MayaPH/GodziLLa2-70B",
-    "psmathur/model_007_v2",
-    "chargoddard/MelangeA-70b",
-    "ehartford/Samantha-1.1-70b",
-    "psmathur/model_009",
-    "upstage/Llama-2-70b-instruct",
-    "yeontaek/llama-2-70B-ensemble-v7",
-    "yeontaek/llama-2-70B-ensemble-v6",
-    "chargoddard/MelangeB-70b",
-    "yeontaek/llama-2-70B-ensemble-v3",
-    "chargoddard/MelangeC-70b",
-    "garage-bAInd/Camel-Platypus2-70B",
-    "yeontaek/llama-2-70B-ensemble-v2",
-    "garage-bAInd/Camel-Platypus2-70B",
-    "migtissera/Synthia-70B-v1.2",
-    "v2ray/LLaMA-2-Wizard-70B-QLoRA",
-    "quantumaikr/llama-2-70b-fb16-orca-chat-10k",
-    "v2ray/LLaMA-2-Wizard-70B-QLoRA",
-    "stabilityai/StableBeluga2",
-    "quantumaikr/llama-2-70b-fb16-guanaco-1k",
-    "garage-bAInd/Camel-Platypus2-70B",
-    "migtissera/Synthia-70B-v1.1",
-    "migtissera/Synthia-70B",
-    "psmathur/model_101",
-    "augtoma/qCammel70",
-    "augtoma/qCammel-70",
-    "augtoma/qCammel-70v1",
-    "augtoma/qCammel-70x",
-    "augtoma/qCammel-70-x",
-    "jondurbin/airoboros-l2-70b-gpt4-1.4.1",
-    "dfurman/llama-2-70b-dolphin-peft",
-    "jondurbin/airoboros-l2-70b-2.1",
-    "TheBloke/llama-2-70b-Guanaco-QLoRA-fp16",
-    "quantumaikr/QuantumLM-llama2-70B-Korean-LoRA",
-    "quantumaikr/quantumairk-llama-2-70B-instruct",
-    "psmathur/model_420",
-    "psmathur/model_51",
-    "garage-bAInd/Camel-Platypus2-70B",
-    "TheBloke/Airoboros-L2-70B-2.1-GPTQ",
-    "OpenAssistant/llama2-70b-oasst-sft-v10",
-    "garage-bAInd/Platypus2-70B",
-    "liuxiang886/llama2-70B-qlora-gpt4",
-    "upstage/llama-65b-instruct",
-    "quantumaikr/llama-2-70b-fb16-korean",
-    "NousResearch/Nous-Hermes-Llama2-70b",
-    "v2ray/LLaMA-2-Jannie-70B-QLoRA",
-    "jondurbin/airoboros-l2-70b-gpt4-m2.0",
-    "jondurbin/airoboros-l2-70b-gpt4-m2.0",
-    "OpenAssistant/llama2-70b-oasst-sft-v10",
-    "yeontaek/llama-2-70B-ensemble-v8",
-    "jondurbin/airoboros-l2-70b-gpt4-2.0",
-    "jarradh/llama2_70b_chat_uncensored",
-    "WizardLM/WizardMath-70B-V1.0",
-    "jordiclive/Llama-2-70b-oasst-1-200",
-    "WizardLM/WizardMath-70B-V1.0",
-    "jondurbin/airoboros-l2-70b-gpt4-2.0",
-    "OpenLemur/lemur-70b-chat-v1",
-    "tiiuae/falcon-180B",
-    "tiiuae/falcon-180B",
-    "stabilityai/StableBeluga1-Delta",
-    "psmathur/model_42_70b",
-    "psmathur/test_42_70b",
-    "TheBloke/fiction.live-Kimiko-V2-70B-fp16",
-    "tiiuae/falcon-180B",
-    "WizardLM/WizardMath-70B-V1.0",
-    "tiiuae/falcon-180B-chat",
-    "jondurbin/airoboros-l2-70b-gpt4-2.0",
-    "ehartford/samantha-1.1-llama-33b",
-    "ajibawa-2023/scarlett-33b",
-    "ddobokki/Llama-2-70b-orca-200k",
-    "TheBloke/gpt4-alpaca-lora_mlp-65B-HF",
-    "tiiuae/falcon-180B-chat",
-    "tiiuae/falcon-180B-chat",
-    "tiiuae/falcon-180B",
-    "TheBloke/Lemur-70B-Chat-v1-GPTQ",
-    "NousResearch/Nous-Puffin-70B",
-    "WizardLM/WizardLM-70B-V1.0",
-    "WizardLM/WizardMath-70B-V1.0",
-    "meta-llama/Llama-2-70b-hf",
-    "TheBloke/Llama-2-70B-fp16",
-    "Weyaxi/llama-2-alpacagpt4-1000step",
-    "WizardLM/WizardLM-70B-V1.0",
-    "simsim314/WizardLM-70B-V1.0-HF",
-    "simsim314/WizardLM-70B-V1.0-HF",
-    "WizardLM/WizardLM-70B-V1.0",
-    "openbmb/UltraLM-65b",
-    "psmathur/model_420_preview",
-    "WizardLM/WizardLM-70B-V1.0",
-    "simsim314/WizardLM-70B-V1.0-HF",
-    "OpenBuddy/openbuddy-llama2-70b-v10.1-bf16",
-    "upstage/llama-30b-instruct-2048",
-    "jondurbin/airoboros-65b-gpt4-1.2",
-    "TheBloke/guanaco-65B-HF",
-    "jondurbin/airoboros-65b-gpt4-1.3",
-    "meta-llama/Llama-2-70b-chat-hf",
-    "ValiantLabs/ShiningValiant",
-    "Faradaylab/Aria-70B",
-    "lilloukas/GPlatty-30B",
-    "TheBloke/VicUnlocked-alpaca-65B-QLoRA-fp16",
-    "jondurbin/airoboros-65b-gpt4-1.4-peft",
-    "jondurbin/airoboros-65b-gpt4-1.4",
-    "jondurbin/airoboros-65b-gpt4-2.0",
-    "TheBloke/WizardLM-70B-V1.0-GPTQ",
-    "TheBloke/WizardLM-70B-V1.0-GPTQ",
-    "ariellee/SuperPlatty-30B",
-    "jondurbin/airoboros-65b-gpt4-1.4",
-    "jondurbin/airoboros-65b-gpt4-2.0",
-    "yeontaek/llama-2-70b-IA3-guanaco",
-    "CalderaAI/30B-Lazarus",
-    "Aspik101/trurl-2-13b-pl-instruct_unload",
-    "ehartford/WizardLM-33B-V1.0-Uncensored",
-    "ehartford/WizardLM-33B-V1.0-Uncensored",
-    "OpenBuddy/openbuddy-llama-65b-v8-bf16",
-    "Aspik101/llama-30b-instruct-2048-PL-lora",
-    "h2oai/h2ogpt-research-oasst1-llama-65b",
-    "Aspik101/llama-30b-instruct-2048-PL-lora",
-    "CalderaAI/30B-Epsilon",
-    "Aspik101/llama-30b-2048-instruct-PL-lora_unload",
-    "jondurbin/airoboros-65b-gpt4-m2.0",
-    "jondurbin/airoboros-65b-gpt4-m2.0",
-    "Aeala/Alpaca-elina-65b",
-    "TheBloke/robin-65b-v2-fp16",
-    "TheBloke/gpt4-alpaca-lora-30b-HF",
-    "TheBloke/Llama-2-70B-chat-GPTQ",
-    "upstage/llama-30b-instruct",
-    "OpenLemur/lemur-70b-v1",
-    "lmsys/vicuna-33b-v1.3",
-    "ausboss/llama-30b-supercot",
-    "ai-business/Luban-13B",
-    "Henk717/airochronos-33B",
-    "lmsys/vicuna-33b-v1.3",
-    "Henk717/airochronos-33B",
-    "bavest/fin-llama-33b-merged",
-    "jondurbin/airoboros-33b-gpt4-1.4",
-    "YeungNLP/firefly-llama-30b",
-    "Aspik101/30B-Lazarus-instruct-PL-lora_unload",
-    "uukuguy/speechless-llama2-luban-orca-platypus-13b",
-    "xxyyy123/test_merge_p_ov1_w0.66_w0.5_n1",
-    "jondurbin/airoboros-33b-gpt4-1.2",
-    "TheBloke/alpaca-lora-65B-HF",
-    "bofenghuang/vigogne-33b-instruct",
-    "yeontaek/llama-2-13B-ensemble-v5",
-    "garage-bAInd/Platypus-30B",
-    "Open-Orca/OpenOrca-Platypus2-13B",
-    "kajdun/viwaai-30b_v4",
-    "lilloukas/Platypus-30B",
-    "Open-Orca/OpenOrca-Platypus2-13B",
-    "Henk717/chronoboros-33B",
-    "jondurbin/airoboros-33b-2.1",
-    "HiTZ/alpaca-lora-65b-en-pt-es-ca",
-    "quantumaikr/QuantumLM-70B-hf",
-    "uukuguy/speechless-llama2-13b",
-    "uukuguy/speechless-llama2-hermes-orca-platypus-13b",
-    "openaccess-ai-collective/manticore-30b-chat-pyg-alpha",
-    "LLMs/WizardLM-30B-V1.0",
-    "TheBloke/WizardLM-30B-fp16",
-    "openaccess-ai-collective/hippogriff-30b-chat",
-    "concedo/Vicuzard-30B-Uncensored",
-    "TFLai/OpenOrca-Platypus2-13B-QLoRA-0.80-epoch",
-    "huggingface/llama-65b",
-    "huggyllama/llama-65b",
-    "gaodrew/gaodrew-llama-30b-instruct-2048-Open-Platypus-100steps",
-    "uukuguy/speechless-llama2-hermes-orca-platypus-wizardlm-13b",
-    "Sao10K/Mythical-Destroyer-V2-L2-13B",
-    "camel-ai/CAMEL-33B-Combined-Data",
-    "dsvv-cair/alpaca-cleaned-llama-30b-bf16",
-    "MetaIX/GPT4-X-Alpasta-30b",
-    "garage-bAInd/Stable-Platypus2-13B",
-    "TFLai/Luban-Platypus2-13B-QLora-0.80-epoch",
-    "TheBloke/OpenOrca-Platypus2-13B-GPTQ",
-    "IkariDev/Athena-tmp",
-    "OpenBuddyEA/openbuddy-llama-30b-v7.1-bf16",
-    "OpenBuddyEA/openbuddy-llama-30b-v7.1-bf16",
-    "Open-Orca/OpenOrcaxOpenChat-Preview2-13B",
-    "psmathur/model_007_13b_v2",
-    "Aspik101/Vicuzard-30B-Uncensored-instruct-PL-lora_unload",
-    "jondurbin/airoboros-33b-gpt4-m2.0",
-    "Sao10K/Mythical-Destroyer-L2-13B",
-    "TheBloke/Wizard-Vicuna-30B-Uncensored-fp16",
-    "ehartford/Wizard-Vicuna-30B-Uncensored",
-    "TFLai/Nova-13B",
-    "TheBloke/robin-33B-v2-fp16",
-    "totally-not-an-llm/PuddleJumper-13b",
-    "Aeala/VicUnlocked-alpaca-30b",
-    "Yhyu13/oasst-rlhf-2-llama-30b-7k-steps-hf",
-    "jondurbin/airoboros-33b-gpt4",
-    "jondurbin/airoboros-33b-gpt4-m2.0",
-    "tiiuae/falcon-40b-instruct",
-    "psmathur/orca_mini_v3_13b",
-    "Aeala/GPT4-x-AlpacaDente-30b",
-    "MayaPH/GodziLLa-30B",
-    "jondurbin/airoboros-33b-gpt4-m2.0",
-    "TFLai/SpeechlessV1-Nova-13B",
-    "yeontaek/llama-2-13B-ensemble-v4",
-    "ajibawa-2023/carl-33b",
-    "jondurbin/airoboros-33b-gpt4-2.0",
-    "TFLai/Stable-Platypus2-13B-QLoRA-0.80-epoch",
-    "jondurbin/airoboros-33b-gpt4-1.3",
-    "TehVenom/oasst-sft-6-llama-33b-xor-MERGED-16bit",
-    "TFLai/OrcaMini-Platypus2-13B-QLoRA-0.80-epoch",
-    "jondurbin/airoboros-33b-gpt4-2.0",
-    "chargoddard/Chronorctypus-Limarobormes-13b",
-    "jondurbin/airoboros-33b-gpt4-1.3",
-    "Open-Orca/OpenOrca-Platypus2-13B",
-    "FelixChao/vicuna-33b-coder",
-    "FelixChao/vicuna-33b-coder",
-    "Gryphe/MythoMix-L2-13b",
-    "Aeala/Enterredaas-33b",
-    "yeontaek/llama-2-13B-ensemble-v1",
-    "TFLai/OpenOrcaPlatypus2-Platypus2-13B-QLora-0.80-epoch",
-    "TFLai/Ensemble5-Platypus2-13B-QLora-0.80-epoch",
-    "yeontaek/llama-2-13B-ensemble-v3",
-    "TFLai/MythoMix-Platypus2-13B-QLoRA-0.80-epoch",
-    "yihan6324/llama2-13b-instructmining-40k-sharegpt",
-    "timdettmers/guanaco-33b-merged",
-    "TFLai/EnsembleV5-Nova-13B",
-    "circulus/Llama-2-13b-orca-v1",
-    "Undi95/ReMM-SLERP-L2-13B",
-    "Gryphe/MythoMax-L2-13b",
-    "stabilityai/StableBeluga-13B",
-    "circulus/Llama-2-13b-orca-v1",
-    "ehartford/WizardLM-30B-Uncensored",
-    "The-Face-Of-Goonery/huginnv1.2",
-    "TheBloke/OpenOrcaxOpenChat-Preview2-13B-GPTQ",
-    "Sao10K/Stheno-L2-13B",
-    "bofenghuang/vigogne-2-13b-instruct",
-    "The-Face-Of-Goonery/Huginn-13b-FP16",
-    "grimpep/L2-MythoMax22b-instruct-Falseblock",
-    "TFLai/Nous-Hermes-Platypus2-13B-QLoRA-0.80-epoch",
-    "yeontaek/Platypus2xOpenOrca-13B-IA3-v4",
-    "yeontaek/Platypus2xOpenOrca-13B-IA3",
-    "yeontaek/Platypus2xOpenOrca-13B-IA3-ensemble",
-    "Open-Orca/LlongOrca-13B-16k",
-    "Sao10K/Stheno-Inverted-L2-13B",
-    "garage-bAInd/Camel-Platypus2-13B",
-    "digitous/Alpacino30b",
-    "NousResearch/Nous-Hermes-Llama2-13b",
-    "yeontaek/Platypus2xOpenOrca-13B-IA3-v3",
-    "TFLai/MythicalDestroyerV2-Platypus2-13B-QLora-0.80-epoch",
-    "TheBloke/VicUnlocked-30B-LoRA-HF",
-    "Undi95/Nous-Hermes-13B-Code",
-    "The-Face-Of-Goonery/Chronos-Beluga-v2-13bfp16",
-    "NousResearch/Nous-Hermes-Llama2-13b",
-    "Monero/WizardLM-Uncensored-SuperCOT-StoryTelling-30b",
-    "TheBloke/Wizard-Vicuna-30B-Uncensored-GPTQ",
-    "Open-Orca/OpenOrcaxOpenChat-Preview2-13B",
-    "Austism/chronos-hermes-13b-v2",
-    "yeontaek/Platypus2xOpenOrca-13B-IA3-v2.1",
-    "yeontaek/Platypus2xOpenOrca-13B-IA3-v2",
-    "Gryphe/MythoLogic-L2-13b",
-    "augtoma/qCammel-13",
-    "YeungNLP/firefly-llama2-13b-v1.2",
-    "Aspik101/StableBeluga-13B-instruct-PL-lora_unload",
-    "andreaskoepf/llama2-13b-megacode2_min100",
-    "rombodawg/LosslessMegaCoder-llama2-13b-mini",
-    "yulan-team/YuLan-Chat-2-13b-fp16",
-    "elinas/chronos-33b",
-    "YeungNLP/firefly-llama2-13b",
-    "Sao10K/Medusa-13b",
-    "OptimalScale/robin-65b-v2-delta",
-    "minlik/chinese-alpaca-33b-merged",
-    "OpenAssistant/llama2-13b-megacode2-oasst",
-    "TheBloke/OpenAssistant-SFT-7-Llama-30B-HF",
-    "Undi95/UndiMix-v1-13b",
-    "ehartford/Samantha-1.11-13b",
-    "beaugogh/Llama2-13b-sharegpt4",
-    "Aeala/GPT4-x-AlpacaDente2-30b",
-    "luffycodes/nash-vicuna-13b-v1dot5-ep2-w-rag-w-simple",
-    "WizardLM/WizardLM-13B-V1.1",
-    "uukuguy/speechless-orca-platypus-coig-lite-2k-0.6e-13b",
-    "huggyllama/llama-30b",
-    "Undi95/ReMM-L2-13B-PIPPA",
-    "Undi95/ReMM-L2-13B",
-    "gaodrew/gaodrew-gorgonzola-13b",
-    "lmsys/vicuna-13b-v1.5",
-    "yeontaek/Platypus2xOpenOrca-13B-LoRa",
-    "Yhyu13/llama-30B-hf-openassitant",
-    "huggingface/llama-30b",
-    "lmsys/vicuna-13b-v1.5",
-    "TFLai/Athena-Platypus2-13B-QLora-0.80-epoch",
-    "TheBloke/dromedary-65b-lora-HF",
-    "yeontaek/llama-2-13b-Beluga-QLoRA",
-    "The-Face-Of-Goonery/Huginn-13b-V4",
-    "The-Face-Of-Goonery/Huginn-13b-v4.5",
-    "The-Face-Of-Goonery/Huginn-v3-13b",
-    "tiiuae/falcon-40b",
-    "WhoTookMyAmogusNickname/NewHope_HF_not_official",
-    "gaodrew/OpenOrca-Platypus2-13B-thera-1250",
-    "SLAM-group/NewHope",
-    "garage-bAInd/Platypus2-13B",
-    "migtissera/Synthia-13B",
-    "elinas/chronos-13b-v2",
-    "mosaicml/mpt-30b-chat",
-    "CHIH-HUNG/llama-2-13b-OpenOrca_5w",
-    "uukuguy/speechless-hermes-coig-lite-13b",
-    "TheBloke/tulu-30B-fp16",
-    "uukuguy/speechless-hermes-coig-lite-13b",
-    "xDAN-AI/xDAN_13b_l2_lora",
-    "lmsys/vicuna-13b-v1.5-16k",
-    "openchat/openchat_v3.1",
-    "CHIH-HUNG/llama-2-13b-dolphin_5w",
-    "Aspik101/vicuna-13b-v1.5-PL-lora_unload",
-    "Undi95/MLewd-L2-13B",
-    "ehartford/minotaur-llama2-13b-qlora",
-    "kajdun/iubaris-13b-v3",
-    "TFLai/Limarp-Platypus2-13B-QLoRA-0.80-epoch",
-    "openchat/openchat_v3.1",
-    "uukuguy/speechless-orca-platypus-coig-lite-4k-0.6e-13b",
-    "ziqingyang/chinese-alpaca-2-13b",
-    "TFLai/Airboros2.1-Platypus2-13B-QLora-0.80-epoch",
-    "yeontaek/llama-2-13b-Guanaco-QLoRA",
-    "lmsys/vicuna-13b-v1.5-16k",
-    "ehartford/based-30b",
-    "kingbri/airolima-chronos-grad-l2-13B",
-    "openchat/openchat_v3.2",
-    "uukuguy/speechless-orca-platypus-coig-lite-4k-0.5e-13b",
-    "yeontaek/Platypus2-13B-LoRa",
-    "kingbri/chronolima-airo-grad-l2-13B",
-    "openchat/openchat_v3.2",
-    "TFLai/PuddleJumper-Platypus2-13B-QLoRA-0.80-epoch",
-    "shareAI/llama2-13b-Chinese-chat",
-    "ehartford/WizardLM-1.0-Uncensored-Llama2-13b",
-    "Aspik101/Redmond-Puffin-13B-instruct-PL-lora_unload",
-    "yeontaek/llama-2-13B-ensemble-v6",
-    "WizardLM/WizardLM-13B-V1.2",
-    "TheBloke/WizardLM-13B-V1.1-GPTQ",
-    "bhenrym14/airophin-13b-pntk-16k-fp16",
-    "ehartford/WizardLM-1.0-Uncensored-Llama2-13b",
-    "Mikael110/llama-2-13b-guanaco-fp16",
-    "yeontaek/airoboros-2.1-llama-2-13B-QLoRa",
-    "CalderaAI/13B-Legerdemain-L2",
-    "grimpep/llama2-22b-wizard_vicuna",
-    "grimpep/llama2-22B-GPLATTY",
-    "bhenrym14/airophin-13b-pntk-16k-fp16",
-    "yeontaek/llama-2-13b-QLoRA",
-    "OpenAssistant/llama2-13b-orca-8k-3319",
-    "TheBloke/WizardLM-13B-V1-1-SuperHOT-8K-fp16",
-    "duliadotio/dulia-13b-8k-alpha",
-    "Undi95/LewdEngine",
-    "OpenBuddy/openbuddy-llama2-13b-v8.1-fp16",
-    "CHIH-HUNG/llama-2-13b-open_orca_20w",
-    "bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16",
-    "FlagAlpha/Llama2-Chinese-13b-Chat",
-    "LLMs/WizardLM-13B-V1.0",
-    "chansung/gpt4-alpaca-lora-13b-decapoda-1024",
-    "TheBloke/wizardLM-13B-1.0-fp16",
-    "digitous/13B-Chimera",
-    "yeontaek/Platypus2xOpenOrcaxGuanaco-13B-LoRa",
-    "jondurbin/airoboros-l2-13b-2.1",
-    "Monero/WizardLM-30B-Uncensored-Guanaco-SuperCOT-30b",
-    "TheBloke/UltraLM-13B-fp16",
-    "openaccess-ai-collective/minotaur-13b-fixed",
-    "NousResearch/Redmond-Puffin-13B",
-    "KoboldAI/LLaMA2-13B-Holomax",
-    "Lajonbot/WizardLM-13B-V1.2-PL-lora_unload",
-    "yeontaek/Platypus2-13B-LoRa-v2",
-    "TheBloke/airoboros-13B-HF",
-    "jondurbin/airoboros-13b",
-    "jjaaaww/posi_13b",
-    "CoolWP/llama-2-13b-guanaco-fp16",
-    "yeontaek/Platypus2-13B-QLoRa",
-    "h2oai/h2ogpt-research-oig-oasst1-512-30b",
-    "dfurman/llama-2-13b-guanaco-peft",
-    "NousResearch/Redmond-Puffin-13B",
-    "pe-nlp/llama-2-13b-platypus-vicuna-wizard",
-    "CHIH-HUNG/llama-2-13b-dolphin_20w",
-    "NousResearch/Nous-Hermes-13b",
-    "NobodyExistsOnTheInternet/GiftedConvo13bLoraNoEconsE4",
-    "ehartford/Wizard-Vicuna-13B-Uncensored",
-    "TheBloke/Wizard-Vicuna-13B-Uncensored-HF",
-    "openchat/openchat_v3.2_super",
-    "bhenrym14/airophin-v2-13b-PI-8k-fp16",
-    "openaccess-ai-collective/manticore-13b",
-    "The-Face-Of-Goonery/Huginn-22b-Prototype",
-    "jphme/Llama-2-13b-chat-german",
-    "grimpep/llama2-28B-Airo03",
-    "TheBloke/Kimiko-v2-13B-fp16",
-    "FPHam/Free_Sydney_13b_HF",
-    "lmsys/vicuna-13b-v1.3",
-    "FelixChao/llama2-13b-math1.1",
-    "CalderaAI/13B-BlueMethod",
-    "meta-llama/Llama-2-13b-chat-hf",
-    "deepse/CodeUp-Llama-2-13b-chat-hf",
-    "WizardLM/WizardMath-13B-V1.0",
-    "WizardLM/WizardMath-13B-V1.0",
-    "HyperbeeAI/Tulpar-7b-v0",
-    "xxyyy123/test_qkvo_adptor",
-    "xxyyy123/mc_data_30k_from_platpus_orca_7b_10k_v1_lora_qkvo_rank14_v2",
-    "openchat/openchat_v2_w",
-    "FelixChao/llama2-13b-math1.1",
-    "psmathur/orca_mini_v3_7b",
-    "TehVenom/Metharme-13b-Merged",
-    "xxyyy123/10k_v1_lora_qkvo_rank14_v3",
-    "OpenAssistant/llama2-13b-orca-v2-8k-3166",
-    "openaccess-ai-collective/wizard-mega-13b",
-    "jondurbin/airoboros-13b-gpt4-1.4",
-    "jondurbin/airoboros-13b-gpt4-1.4-fp16",
-    "Monero/Manticore-13b-Chat-Pyg-Guanaco",
-    "FelixChao/llama2-13b-math1.2",
-    "chargoddard/platypus-2-22b-relora",
-    "FelixChao/llama2-13b-math1.2",
-    "Gryphe/MythoBoros-13b",
-    "CalderaAI/13B-Ouroboros",
-    "OpenAssistant/llama2-13b-orca-v2-8k-3166",
-    "heegyu/LIMA2-13b-hf",
-    "digitous/13B-HyperMantis",
-    "Gryphe/MythoLogic-13b",
-    "TheBloke/Airoboros-L2-13B-2.1-GPTQ",
-    "chargoddard/platypus2-22b-relora",
-    "openchat/openchat_v2",
-    "yeontaek/Platypus2-13B-IA3",
-    "stabilityai/StableBeluga-7B",
-    "circulus/Llama-2-7b-orca-v1",
-    "budecosystem/genz-13b-v2",
-    "TheBloke/gpt4-x-vicuna-13B-HF",
-    "NobodyExistsOnTheInternet/GiftedConvo13bLoraNoEcons",
-    "zarakiquemparte/zarafusionex-1.1-l2-7b",
-    "Lajonbot/tableBeluga-7B-instruct-pl-lora_unload",
-    "jondurbin/airoboros-13b-gpt4",
-    "gaodrew/gaodrew-gorgonzola-13b",
-    "jondurbin/airoboros-13b-gpt4-1.1",
-    "TheBloke/gpt4-alpaca-lora-13B-HF",
-    "zarakiquemparte/zarablendex-vq-l2-7b",
-    "openaccess-ai-collective/manticore-13b-chat-pyg",
-    "Lajonbot/Llama-2-13b-hf-instruct-pl-lora_unload",
-    "NobodyExistsOnTheInternet/PuffedLIMA13bQLORA",
-    "xxyyy123/10k_v1_lora_qkvo_rank28_v2",
-    "jondurbin/airoboros-l2-13b-gpt4-1.4.1",
-    "dhmeltzer/Llama-2-13b-hf-eli5-wiki-1024_r_64_alpha_16",
-    "NobodyExistsOnTheInternet/PuffedConvo13bLoraE4",
-    "yihan6324/llama2-7b-instructmining-40k-sharegpt",
-    "CHIH-HUNG/llama-2-13b-Open_Platypus_and_ccp_2.6w",
-    "Aeala/GPT4-x-Alpasta-13b",
-    "psmathur/orca_mini_v2_13b",
-    "YeungNLP/firefly-llama-13b",
-    "psmathur/orca_mini_v2_13b",
-    "zarakiquemparte/zarafusionix-l2-7b",
-    "yihan6324/llama2-7b-instructmining-60k-sharegpt",
-    "yihan6324/llama-2-7b-instructmining-60k-sharegpt",
-    "layoric/llama-2-13b-code-alpaca",
-    "bofenghuang/vigogne-13b-instruct",
-    "Lajonbot/vicuna-13b-v1.3-PL-lora_unload",
-    "lvkaokao/llama2-7b-hf-chat-lora-v3",
-    "ehartford/dolphin-llama-13b",
-    "YeungNLP/firefly-llama-13b-v1.2",
-    "TheBloke/Kimiko-13B-fp16",
-    "kevinpro/Vicuna-13B-CoT",
-    "eachadea/vicuna-13b-1.1",
-    "pillowtalks-ai/delta13b",
-    "TheBloke/vicuna-13B-1.1-HF",
-    "TheBloke/Vicuna-13B-CoT-fp16",
-    "lmsys/vicuna-13b-delta-v1.1",
-    "lmsys/vicuna-13b-v1.1",
-    "xxyyy123/20k_v1_lora_qkvo_rank14_v2",
-    "TheBloke/guanaco-13B-HF",
-    "TheBloke/vicuna-13b-v1.3.0-GPTQ",
-    "edor/Stable-Platypus2-mini-7B",
-    "totally-not-an-llm/EverythingLM-13b-V2-16k",
-    "zarakiquemparte/zaraxe-l2-7b",
-    "beaugogh/Llama2-7b-openorca-mc-v2",
-    "TheBloke/Nous-Hermes-13B-SuperHOT-8K-fp16",
-    "quantumaikr/QuantumLM",
-    "jondurbin/airoboros-13b-gpt4-1.2",
-    "TheBloke/robin-13B-v2-fp16",
-    "TFLai/llama-2-13b-4bit-alpaca-gpt4",
-    "yihan6324/llama2-7b-instructmining-orca-40k",
-    "dvruette/oasst-llama-13b-2-epochs",
-    "Open-Orca/LlongOrca-7B-16k",
-    "Aspik101/Nous-Hermes-13b-pl-lora_unload",
-    "ehartford/Samantha-1.11-CodeLlama-34b",
-    "nkpz/llama2-22b-chat-wizard-uncensored",
-    "bofenghuang/vigogne-13b-chat",
-    "beaugogh/Llama2-7b-openorca-mc-v1",
-    "OptimalScale/robin-13b-v2-delta",
-    "pe-nlp/llama-2-13b-vicuna-wizard",
-    "chargoddard/llama2-22b",
-    "gywy/llama2-13b-chinese-v1",
-    "frank098/Wizard-Vicuna-13B-juniper",
-    "IGeniusDev/llama13B-quant8-testv1-openorca-customdataset",
-    "CHIH-HUNG/llama-2-13b-huangyt_Fintune_1_17w-gate_up_down_proj",
-    "eachadea/vicuna-13b",
-    "yihan6324/llama2-7b-instructmining-orca-90k",
-    "chargoddard/llama2-22b-blocktriangular",
-    "luffycodes/mcq-vicuna-13b-v1.5",
-    "Yhyu13/chimera-inst-chat-13b-hf",
-    "luffycodes/mcq-vicuna-13b-v1.5",
-    "chargoddard/ypotryll-22b-epoch2-qlora",
-    "totally-not-an-llm/EverythingLM-13b-16k",
-    "luffycodes/mcq-hal-vicuna-13b-v1.5",
-    "openaccess-ai-collective/minotaur-13b",
-    "IGeniusDev/llama13B-quant8-testv1-openorca-customdataset",
-    "chargoddard/llama2-22b-blocktriangular",
-    "TFLai/Platypus2-13B-QLoRA-0.80-epoch",
-    "meta-llama/Llama-2-13b-hf",
-    "CHIH-HUNG/llama-2-13b-huangyt_FINETUNE2_3w-gate_up_down_proj",
-    "luffycodes/mcq-hal-vicuna-13b-v1.5",
-    "TheBloke/Llama-2-13B-fp16",
-    "TaylorAI/Flash-Llama-13B",
-    "shareAI/bimoGPT-llama2-13b",
-    "wahaha1987/llama_13b_sharegpt94k_fastchat",
-    "openchat/openchat_8192",
-    "CHIH-HUNG/llama-2-13b-huangyt_Fintune_1_17w-q_k_v_o_proj",
-    "dvruette/llama-13b-pretrained-sft-do2",
-    "CHIH-HUNG/llama-2-13b-alpaca-test",
-    "OpenBuddy/openbuddy-llama2-13b-v11.1-bf16",
-    "CHIH-HUNG/llama-2-13b-FINETUNE2_TEST_2.2w",
-    "project-baize/baize-v2-13b",
-    "jondurbin/airoboros-l2-13b-gpt4-m2.0",
-    "yeontaek/Platypus2xOpenOrca-13B-LoRa-v2",
-    "CHIH-HUNG/llama-2-13b-huangyt_FINETUNE2_3w",
-    "xzuyn/Alpacino-SuperCOT-13B",
-    "jondurbin/airoboros-l2-13b-gpt4-2.0",
-    "aiplanet/effi-13b",
-    "clibrain/Llama-2-13b-ft-instruct-es",
-    "CHIH-HUNG/llama-2-13b-huangyt_Fintune_1_17w",
-    "bofenghuang/vigogne-2-7b-instruct",
-    "CHIH-HUNG/llama-2-13b-huangyt_FINETUNE2_3w-q_k_v_o_proj",
-    "bofenghuang/vigogne-2-7b-chat",
-    "aiplanet/effi-13b",
-    "haonan-li/bactrian-x-llama-13b-merged",
-    "beaugogh/Llama2-7b-sharegpt4",
-    "HWERI/Llama2-7b-sharegpt4",
-    "jondurbin/airoboros-13b-gpt4-1.3",
-    "jondurbin/airoboros-c34b-2.1",
-    "junelee/wizard-vicuna-13b",
-    "TheBloke/wizard-vicuna-13B-HF",
-    "Open-Orca/OpenOrca-Preview1-13B",
-    "TheBloke/h2ogpt-oasst1-512-30B-HF",
-    "TheBloke/Llama-2-13B-GPTQ",
-    "camel-ai/CAMEL-13B-Combined-Data",
-    "lmsys/vicuna-7b-v1.5",
-    "lmsys/vicuna-7b-v1.5-16k",
-    "lmsys/vicuna-7b-v1.5",
-    "ausboss/llama-13b-supercot",
-    "TheBloke/tulu-13B-fp16",
-    "NousResearch/Nous-Hermes-llama-2-7b",
-    "jlevin/guanaco-13b-llama-2",
-    "lmsys/vicuna-7b-v1.5-16k",
-    "dvruette/llama-13b-pretrained",
-    "nkpz/llama2-22b-daydreamer-v3",
-    "dvruette/llama-13b-pretrained-dropout",
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-    "Danielbrdz/Barcenas-7b",
-    "heegyu/WizardVicuna2-13b-hf",
-    "meta-llama/Llama-2-7b-chat-hf",
-    "PeanutJar/LLaMa-2-PeanutButter_v14-7B",
-    "PeanutJar/LLaMa-2-PeanutButter_v4-7B",
-    "davzoku/cria-llama2-7b-v1.3",
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-    "garage-bAInd/Platypus2-7B",
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-    "mosaicml/mpt-30b",
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-    "huggingface/llama-13b",
-    "dvruette/oasst-llama-13b-1000-steps",
-    "jordiclive/gpt4all-alpaca-oa-codealpaca-lora-13b",
-    "huggyllama/llama-13b",
-    "Voicelab/trurl-2-7b",
-    "TFLai/llama-13b-4bit-alpaca",
-    "gywy/llama2-13b-chinese-v2",
-    "lmsys/longchat-13b-16k",
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-    "WizardLM/WizardMath-7B-V1.0",
-    "Norquinal/llama-2-7b-claude-chat",
-    "TheTravellingEngineer/llama2-7b-chat-hf-dpo",
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-    "conceptofmind/LLongMA-2-13b-16k",
-    "tianyil1/denas-llama2",
-    "lmsys/vicuna-7b-v1.3",
-    "conceptofmind/LLongMA-2-13b-16k",
-    "openchat/opencoderplus",
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-    "heegyu/LIMA2-7b-hf",
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-    "abhishek/llama2guanacotest",
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-    "llama-anon/instruct-13b",
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-    "shibing624/chinese-alpaca-plus-13b-hf",
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-    "quantumaikr/llama-2-7b-hf-guanaco-1k",
-    "togethercomputer/Llama-2-7B-32K-Instruct",
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-    "jondurbin/airoboros-l2-7b-gpt4-1.4.1",
-    "wahaha1987/llama_7b_sharegpt94k_fastchat",
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-    "chaoyi-wu/MedLLaMA_13B",
-    "edor/Platypus2-mini-7B",
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-    "venkycs/llama-v2-7b-32kC-Security",
-    "psyche/kollama2-7b",
-    "Fredithefish/Guanaco-7B-Uncensored",
-    "TheTravellingEngineer/llama2-7b-chat-hf-guanaco",
-    "ehartford/WizardLM-13B-Uncensored",
-    "PocketDoc/Dans-CreepingSenseOfDoom",
-    "wenge-research/yayi-7b-llama2",
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-    "TinyPixel/lima-test",
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-    "lgaalves/llama-2-7b-hf_open-platypus",
-    "ziqingyang/chinese-alpaca-2-7b",
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-    "meta-llama/Llama-2-7b-hf",
-    "bongchoi/test-llama2-7b",
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-    "dhmeltzer/llama-7b-SFT_ds_wiki65k_1024_r_64_alpha_16_merged",
-    "bofenghuang/vigogne-7b-chat",
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-    "jondurbin/airoboros-l2-7b-gpt4-m2.0",
-    "synapsoft/Llama-2-7b-chat-hf-flan2022-1.2M",
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-    "Charlie911/vicuna-7b-v1.5-lora-mctaco",
-    "yihan6324/instructmining-platypus-15k",
-    "meta-llama/Llama-2-7b-hf",
-    "TheTravellingEngineer/llama2-7b-chat-hf-v3",
-    "quantumaikr/KoreanLM-hf",
-    "openthaigpt/openthaigpt-1.0.0-alpha-7b-chat-ckpt-hf",
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-    "ehartford/Wizard-Vicuna-7B-Uncensored",
-    "TheBloke/Wizard-Vicuna-7B-Uncensored-HF",
-    "TheTravellingEngineer/llama2-7b-chat-hf-v3",
-    "golaxy/gowizardlm",
-    "ehartford/dolphin-llama2-7b",
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-    "notstoic/PygmalionCoT-7b",
-    "golaxy/gogpt2-13b",
-    "golaxy/gogpt2-13b-chat",
-    "togethercomputer/LLaMA-2-7B-32K",
-    "TheBloke/wizardLM-7B-HF",
-    "keyfan/vicuna-chinese-replication-v1.1",
-    "golaxy/gogpt2-7b",
-    "aiplanet/effi-7b",
-    "arver/llama7b-qlora",
-    "titan087/OpenLlama13B-Guanaco",
-    "chavinlo/alpaca-native",
-    "project-baize/baize-healthcare-lora-7B",
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-    "golaxy/gogpt-7b",
-    "togethercomputer/LLaMA-2-7B-32K",
-    "yhyhy3/open_llama_7b_v2_med_instruct",
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-    "conceptofmind/LLongMA-2-7b-16k",
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-    "jondurbin/airoboros-7b-gpt4-1.4.1-qlora",
-    "wannaphong/openthaigpt-0.1.0-beta-full-model_for_open_llm_leaderboard",
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-    "project-baize/baize-v2-7b",
-    "LMFlow/Robin-v2",
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-    "OptimalScale/robin-7b-v2-delta",
-    "uukuguy/speechless-codellama-platypus-13b",
-    "jerryjalapeno/nart-100k-7b",
-    "wenge-research/yayi-13b-llama2",
-    "fireballoon/baichuan-vicuna-chinese-7b",
-    "jlevin/guanaco-unchained-llama-2-7b",
-    "csitfun/llama-7b-logicot",
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-    "WeOpenML/PandaLM-Alpaca-7B-v1",
-    "illuin/test-custom-llama",
-    "yeontaek/WizardCoder-Python-13B-LoRa",
-    "ashercn97/giraffe-7b",
-    "mosaicml/mpt-7b-chat",
-    "abhishek/autotrain-llama-alpaca-peft-52508123785",
-    "Neko-Institute-of-Science/pygmalion-7b",
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-    "TheBloke/Planner-7B-fp16",
-    "shibing624/chinese-llama-plus-13b-hf",
-    "AGI-inc/lora_moe_7b_baseline",
-    "DevaMalla/llama-base-7b",
-    "AGI-inc/lora_moe_7b",
-    "togethercomputer/GPT-JT-6B-v0",
-    "ehartford/WizardLM-7B-Uncensored",
-    "shibing624/chinese-alpaca-plus-7b-hf",
-    "beomi/llama-2-ko-7b",
-    "mosaicml/mpt-7b-8k-instruct",
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-    "mosaicml/mpt-7b-instruct",
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-    "WeOpenML/Alpaca-7B-v1",
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-    "codellama/CodeLlama-13b-Instruct-hf",
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-    "openlm-research/open_llama_7b_v2",
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-    "togethercomputer/GPT-JT-6B-v1",
-    "TheBloke/koala-7B-HF",
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-    "nathan0/mpt_delta_tuned_model_v2",
-    "GeorgiaTechResearchInstitute/galpaca-30b",
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-    "shareAI/CodeLLaMA-chat-13b-Chinese",
-    "TigerResearch/tigerbot-7b-sft",
-    "Writer/InstructPalmyra-20b",
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-    "VMware/open-llama-7b-open-instruct",
-    "baichuan-inc/Baichuan-7B",
-    "anas-awadalla/mpt-7b",
-    "mosaicml/mpt-7b",
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-    "OpenAssistant/codellama-13b-oasst-sft-v10",
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-    "togethercomputer/RedPajama-INCITE-Instruct-7B-v0.1",
-    "togethercomputer/RedPajama-INCITE-7B-Instruct",
-    "TheBloke/landmark-attention-llama7b-fp16",
-    "togethercomputer/GPT-JT-Moderation-6B",
-    "h2oai/h2ogpt-gm-oasst1-en-1024-20b",
-    "dvruette/gpt-neox-20b-full-precision",
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-    "dvruette/oasst-gpt-neox-20b-1000-steps",
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-    "TehVenom/PPO_Pygway-V8p4_Dev-6b",
-    "TFLai/gpt-neox-20b-4bit-alpaca",
-    "Corianas/gpt-j-6B-Dolly",
-    "TehVenom/Dolly_Shygmalion-6b",
-    "digitous/Janin-GPTJ",
-    "TehVenom/GPT-J-Pyg_PPO-6B-Dev-V8p4",
-    "EleutherAI/gpt-j-6b",
-    "KoboldAI/GPT-J-6B-Shinen",
-    "TehVenom/Dolly_Malion-6b",
-    "TehVenom/ChanMalion",
-    "Salesforce/codegen-6B-nl",
-    "Fredithefish/RedPajama-INCITE-Chat-3B-Instruction-Tuning-with-GPT-4",
-    "KoboldAI/GPT-J-6B-Janeway",
-    "togethercomputer/RedPajama-INCITE-Chat-3B-v1",
-    "togethercomputer/Pythia-Chat-Base-7B",
-    "heegyu/RedTulu-Uncensored-3B-0719",
-    "KoboldAI/PPO_Pygway-6b-Mix",
-    "KoboldAI/OPT-13B-Erebus",
-    "KoboldAI/fairseq-dense-6.7B",
-    "EleutherAI/pythia-12b-deduped",
-    "pszemraj/pythia-6.9b-HC3",
-    "Fredithefish/Guanaco-3B-Uncensored-v2",
-    "facebook/opt-13b",
-    "TehVenom/GPT-J-Pyg_PPO-6B",
-    "EleutherAI/pythia-6.9b-deduped",
-    "Devio/test-1400",
-    "Fredithefish/Guanaco-3B-Uncensored",
-    "codellama/CodeLlama-7b-hf",
-    "acrastt/RedPajama-INCITE-Chat-Instruct-3B-V1",
-    "Fredithefish/ScarletPajama-3B-HF",
-    "KoboldAI/OPT-13B-Nerybus-Mix",
-    "YeungNLP/firefly-bloom-7b1",
-    "DanielSc4/RedPajama-INCITE-Chat-3B-v1-RL-LoRA-8bit-test1",
-    "klosax/open_llama_7b_400bt_preview",
-    "KoboldAI/OPT-13B-Nerys-v2",
-    "TehVenom/PPO_Shygmalion-6b",
-    "amazon/LightGPT",
-    "KnutJaegersberg/black_goo_recipe_c",
-    "NousResearch/CodeLlama-7b-hf",
-    "togethercomputer/RedPajama-INCITE-Instruct-3B-v1",
-    "heegyu/WizardVicuna-open-llama-3b-v2",
-    "bigscience/bloom-7b1",
-    "Devio/test-22B",
-    "RWKV/rwkv-raven-7b",
-    "hakurei/instruct-12b",
-    "CobraMamba/mamba-gpt-3b",
-    "KnutJaegersberg/black_goo_recipe_a",
-    "acrastt/OmegLLaMA-3B",
-    "codellama/CodeLlama-7b-Instruct-hf",
-    "h2oai/h2ogpt-oig-oasst1-512-6_9b",
-    "KoboldAI/OPT-6.7B-Erebus",
-    "facebook/opt-6.7b",
-    "KnutJaegersberg/black_goo_recipe_d",
-    "KnutJaegersberg/LLongMA-3b-LIMA",
-    "KnutJaegersberg/black_goo_recipe_b",
-    "KoboldAI/OPT-6.7B-Nerybus-Mix",
-    "health360/Healix-3B",
-    "EleutherAI/pythia-12b",
-    "Fredithefish/RedPajama-INCITE-Chat-3B-ShareGPT-11K",
-    "GeorgiaTechResearchInstitute/galactica-6.7b-evol-instruct-70k",
-    "h2oai/h2ogpt-oig-oasst1-256-6_9b",
-    "ikala/bloom-zh-3b-chat",
-    "Taekyoon/llama2-ko-7b-test",
-    "anhnv125/pygmalion-6b-roleplay",
-    "TehVenom/DiffMerge_Pygmalion_Main-onto-V8P4",
-    "KoboldAI/OPT-6B-nerys-v2",
-    "Lazycuber/pyg-instruct-wizardlm",
-    "Devio/testC",
-    "KoboldAI/OPT-30B-Erebus",
-    "Fredithefish/CrimsonPajama",
-    "togethercomputer/RedPajama-INCITE-Base-3B-v1",
-    "bigscience/bloomz-3b",
-    "conceptofmind/Open-LLongMA-3b",
-    "RWKV/rwkv-4-7b-pile",
-    "openlm-research/open_llama_3b",
-    "ewof/koishi-instruct-3b",
-    "DanielSc4/RedPajama-INCITE-Chat-3B-v1-FT-LoRA-8bit-test1",
-    "cerebras/Cerebras-GPT-13B",
-    "EleutherAI/pythia-6.7b",
-    "aisquared/chopt-2_7b",
-    "Azure99/blossom-v1-3b",
-    "PSanni/Deer-3b",
-    "bertin-project/bertin-gpt-j-6B-alpaca",
-    "OpenBuddy/openbuddy-openllama-3b-v10-bf16",
-    "KoboldAI/fairseq-dense-2.7B",
-    "ehartford/CodeLlama-34b-Instruct-hf",
-    "codellama/CodeLlama-34b-Instruct-hf",
-    "TheBloke/CodeLlama-34B-Instruct-fp16",
-    "h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b-preview-300bt-v2",
-    "openlm-research/open_llama_7b_700bt_preview",
-    "NbAiLab/nb-gpt-j-6B-alpaca",
-    "KoboldAI/OPT-2.7B-Erebus",
-    "Writer/camel-5b-hf",
-    "EleutherAI/pythia-2.7b",
-    "facebook/xglm-7.5B",
-    "EleutherAI/pythia-2.8b-deduped",
-    "klosax/open_llama_3b_350bt_preview",
-    "klosax/openllama-3b-350bt",
-    "KoboldAI/OPT-2.7B-Nerybus-Mix",
-    "KoboldAI/GPT-J-6B-Adventure",
-    "cerebras/Cerebras-GPT-6.7B",
-    "TFLai/pythia-2.8b-4bit-alpaca",
-    "facebook/opt-2.7b",
-    "KoboldAI/OPT-2.7B-Nerys-v2",
-    "bigscience/bloom-3b",
-    "Devio/test100",
-    "RWKV/rwkv-raven-3b",
-    "Azure99/blossom-v2-3b",
-    "codellama/CodeLlama-34b-Python-hf",
-    "bhenrym14/airoboros-33b-gpt4-1.4.1-PI-8192-fp16",
-    "EleutherAI/gpt-neo-2.7B",
-    "danielhanchen/open_llama_3b_600bt_preview",
-    "HuggingFaceH4/starchat-alpha",
-    "pythainlp/wangchanglm-7.5B-sft-en-sharded",
-    "beaugogh/pythia-1.4b-deduped-sharegpt",
-    "HWERI/pythia-1.4b-deduped-sharegpt",
-    "OpenAssistant/stablelm-7b-sft-v7-epoch-3",
-    "codellama/CodeLlama-7b-Python-hf",
-    "aisquared/chopt-1_3b",
-    "PygmalionAI/metharme-1.3b",
-    "Linly-AI/Chinese-LLaMA-2-13B-hf",
-    "chargoddard/llama-2-34b-uncode",
-    "RWKV/rwkv-4-3b-pile",
-    "pythainlp/wangchanglm-7.5B-sft-enth",
-    "MBZUAI/LaMini-GPT-1.5B",
-    "Writer/palmyra-base",
-    "KoboldAI/fairseq-dense-1.3B",
-    "EleutherAI/pythia-1.4b-deduped",
-    "MBZUAI/lamini-neo-1.3b",
-    "h2oai/h2ogpt-gm-oasst1-en-2048-open-llama-7b-preview-300bt",
-    "sartmis1/starcoder-finetune-openapi",
-    "MayaPH/opt-flan-iml-6.7b",
-    "facebook/xglm-4.5B",
-    "WizardLM/WizardCoder-15B-V1.0",
-    "facebook/opt-iml-max-1.3b",
-    "stabilityai/stablelm-tuned-alpha-7b",
-    "aisquared/dlite-v2-1_5b",
-    "stabilityai/stablelm-base-alpha-7b",
-    "sartmis1/starcoder-finetune-selfinstruct",
-    "lizhuang144/starcoder_mirror",
-    "bigcode/starcoder",
-    "TheBloke/CodeLlama-34B-Python-fp16",
-    "open-llm-leaderboard/bloomz-1b7-4bit-alpaca-auto-eval-adapter-applied",
-    "ehartford/CodeLlama-34b-Python-hf",
-    "codellama/CodeLlama-7b-Python-hf",
-    "GeorgiaTechResearchInstitute/starcoder-gpteacher-code-instruct",
-    "LoupGarou/WizardCoder-Guanaco-15B-V1.0",
-    "golaxy/gogpt-3b-bloom",
-    "EleutherAI/pythia-1.3b",
-    "codellama/CodeLlama-13b-Python-hf",
-    "hakurei/lotus-12B",
-    "NYTK/PULI-GPTrio",
-    "facebook/opt-1.3b",
-    "TheBloke/CodeLlama-13B-Python-fp16",
-    "codellama/CodeLlama-13b-Python-hf",
-    "RWKV/rwkv-raven-1b5",
-    "PygmalionAI/pygmalion-2.7b",
-    "bigscience/bloom-1b7",
-    "gpt2-xl",
-    "LoupGarou/WizardCoder-Guanaco-15B-V1.1",
-    "RWKV/rwkv-4-1b5-pile",
-    "codellama/CodeLlama-34b-hf",
-    "NousResearch/CodeLlama-34b-hf",
-    "rinna/bilingual-gpt-neox-4b-8k",
-    "lxe/Cerebras-GPT-2.7B-Alpaca-SP",
-    "cerebras/Cerebras-GPT-2.7B",
-    "jzjiao/opt-1.3b-rlhf",
-    "EleutherAI/gpt-neo-1.3B",
-    "aisquared/dlite-v1-1_5b",
-    "Corianas/Quokka_2.7b",
-    "MrNJK/gpt2-xl-sft",
-    "facebook/galactica-1.3b",
-    "aisquared/dlite-v2-774m",
-    "EleutherAI/pythia-1b-deduped",
-    "Kunhao/pile-7b-250b-tokens",
-    "w601sxs/b1ade-1b",
-    "rinna/bilingual-gpt-neox-4b",
-    "shaohang/SparseOPT-1.3B",
-    "shaohang/Sparse0.5_OPT-1.3",
-    "EleutherAI/polyglot-ko-12.8b",
-    "Salesforce/codegen-6B-multi",
-    "bigscience/bloom-1b1",
-    "TFLai/gpt-neo-1.3B-4bit-alpaca",
-    "FabbriSimo01/Bloom_1b_Quantized",
-    "MBZUAI/LaMini-GPT-774M",
-    "Locutusque/gpt2-large-conversational",
-    "Devio/test-3b",
-    "stabilityai/stablelm-tuned-alpha-3b",
-    "PygmalionAI/pygmalion-1.3b",
-    "KoboldAI/fairseq-dense-355M",
-    "Rachneet/gpt2-xl-alpaca",
-    "gpt2-large",
-    "Mikivis/gpt2-large-lora-sft",
-    "stabilityai/stablelm-base-alpha-3b",
-    "gpt2-medium",
-    "Kunhao/pile-7b",
-    "aisquared/dlite-v1-774m",
-    "aisquared/dlite-v2-355m",
-    "YeungNLP/firefly-bloom-2b6-v2",
-    "KnutJaegersberg/gpt-2-xl-EvolInstruct",
-    "KnutJaegersberg/galactica-orca-wizardlm-1.3b",
-    "cerebras/Cerebras-GPT-1.3B",
-    "FabbriSimo01/Cerebras_1.3b_Quantized",
-    "facebook/xglm-1.7B",
-    "EleutherAI/pythia-410m-deduped",
-    "TheBloke/GPlatty-30B-SuperHOT-8K-fp16",
-    "DataLinguistic/DataLinguistic-34B-V1.0",
-    "Corianas/Quokka_1.3b",
-    "TheTravellingEngineer/bloom-560m-RLHF-v2",
-    "Corianas/1.3b",
-    "RWKV/rwkv-4-430m-pile",
-    "porkorbeef/Llama-2-13b-sf",
-    "xhyi/PT_GPTNEO350_ATG",
-    "TheBloke/Wizard-Vicuna-13B-Uncensored-GPTQ",
-    "bigscience/bloomz-560m",
-    "TheBloke/medalpaca-13B-GPTQ-4bit",
-    "TheBloke/Vicuna-33B-1-3-SuperHOT-8K-fp16",
-    "aisquared/dlite-v1-355m",
-    "uukuguy/speechless-codellama-orca-airoboros-13b-0.10e",
-    "yhyhy3/med-orca-instruct-33b",
-    "TheBloke/Wizard-Vicuna-30B-Superhot-8K-fp16",
-    "TheTravellingEngineer/bloom-1b1-RLHF",
-    "MBZUAI/lamini-cerebras-1.3b",
-    "IDEA-CCNL/Ziya-LLaMA-13B-Pretrain-v1",
-    "TheBloke/WizardLM-7B-uncensored-GPTQ",
-    "TheBloke/EverythingLM-13B-16K-GPTQ",
-    "quantumaikr/open_llama_7b_hf",
-    "TheBloke/chronos-wizardlm-uc-scot-st-13B-GPTQ",
-    "TheBloke/WizardLM-30B-Uncensored-GPTQ",
-    "IDEA-CCNL/Ziya-LLaMA-13B-v1",
-    "Phind/Phind-CodeLlama-34B-v1",
-    "robowaifudev/megatron-gpt2-345m",
-    "MayaPH/GodziLLa-30B-instruct",
-    "TheBloke/CAMEL-33B-Combined-Data-SuperHOT-8K-fp16",
-    "uukuguy/speechless-codellama-orca-platypus-13b-0.10e",
-    "doas/test2",
-    "BreadAi/PM_modelV2",
-    "bigcode/santacoder",
-    "TheBloke/wizard-vicuna-13B-GPTQ",
-    "porkorbeef/Llama-2-13b",
-    "TehVenom/DiffMerge-DollyGPT-Pygmalion",
-    "PygmalionAI/pygmalion-350m",
-    "TheBloke/orca_mini_v3_7B-GPTQ",
-    "TheBloke/WizardLM-Uncensored-SuperCOT-StoryTelling-30B-GPTQ",
-    "TheBloke/WizardLM-30B-GPTQ",
-    "bigscience/bloom-560m",
-    "TFLai/gpt2-turkish-uncased",
-    "TheBloke/guanaco-33B-GPTQ",
-    "TheBloke/openchat_v2_openorca_preview-GPTQ",
-    "porkorbeef/Llama-2-13b-public",
-    "TheBloke/LongChat-13B-GPTQ",
-    "yhyhy3/med-orca-instruct-33b",
-    "TheBloke/airoboros-33B-gpt4-1-4-SuperHOT-8K-fp16",
-    "TheBloke/Chinese-Alpaca-33B-SuperHOT-8K-fp16",
-    "MayaPH/FinOPT-Franklin",
-    "TheBloke/WizardLM-33B-V1.0-Uncensored-GPTQ",
-    "TheBloke/Project-Baize-v2-13B-GPTQ",
-    "malhajar/Platypus2-70B-instruct-4bit-gptq",
-    "KoboldAI/OPT-350M-Erebus",
-    "rishiraj/bloom-560m-guanaco",
-    "Panchovix/WizardLM-33B-V1.0-Uncensored-SuperHOT-8k",
-    "doas/test5",
-    "vicgalle/alpaca-7b",
-    "beomi/KoAlpaca-Polyglot-5.8B",
-    "Phind/Phind-CodeLlama-34B-Python-v1",
-    "timdettmers/guanaco-65b-merged",
-    "TheBloke/wizard-mega-13B-GPTQ",
-    "MayaPH/GodziLLa-30B-plus",
-    "TheBloke/Platypus-30B-SuperHOT-8K-fp16",
-    "facebook/opt-350m",
-    "KoboldAI/OPT-350M-Nerys-v2",
-    "TheBloke/robin-33B-v2-GPTQ",
-    "jaspercatapang/Echidna-30B",
-    "TheBloke/llama-30b-supercot-SuperHOT-8K-fp16",
-    "marcchew/test1",
-    "Harshvir/LaMini-Neo-1.3B-Mental-Health_lora",
-    "golaxy/gogpt-560m",
-    "TheBloke/orca_mini_13B-GPTQ",
-    "Panchovix/airoboros-33b-gpt4-1.2-SuperHOT-8k",
-    "Aspik101/tulu-7b-instruct-pl-lora_unload",
-    "Phind/Phind-CodeLlama-34B-v2",
-    "BreadAi/MusePy-1-2",
-    "cerebras/Cerebras-GPT-590M",
-    "microsoft/CodeGPT-small-py",
-    "victor123/WizardLM-13B-1.0",
-    "OptimalScale/robin-65b-v2-delta",
-    "voidful/changpt-bart",
-    "FabbriSimo01/GPT_Large_Quantized",
-    "MayaPH/FinOPT-Lincoln",
-    "KoboldAI/fairseq-dense-125M",
-    "SebastianSchramm/Cerebras-GPT-111M-instruction",
-    "TheTravellingEngineer/bloom-560m-RLHF",
-    "breadlicker45/dough-instruct-base-001",
-    "WizardLM/WizardLM-30B-V1.0",
-    "WizardLM/WizardLM-30B-V1.0",
-    "WizardLM/WizardLM-30B-V1.0",
-    "TaylorAI/Flash-Llama-30M-20001",
-    "porkorbeef/Llama-2-13b-12_153950",
-    "huggingtweets/bladeecity-jerma985",
-    "KnutJaegersberg/megatron-GPT-2-345m-EvolInstruct",
-    "bhenrym14/airoboros-33b-gpt4-1.4.1-lxctx-PI-16384-fp16",
-    "microsoft/DialoGPT-small",
-    "Corianas/590m",
-    "facebook/xglm-564M",
-    "EleutherAI/gpt-neo-125m",
-    "EleutherAI/pythia-160m-deduped",
-    "klosax/pythia-160m-deduped-step92k-193bt",
-    "MBZUAI/lamini-neo-125m",
-    "bigcode/tiny_starcoder_py",
-    "concedo/OPT-19M-ChatSalad",
-    "anton-l/gpt-j-tiny-random",
-    "grantprice/Cerebras-GPT-590M-finetuned-DND",
-    "deepnight-research/zsc-text",
-    "WangZeJun/bloom-820m-chat",
-    "cerebras/Cerebras-GPT-256M",
-    "ai-forever/rugpt3large_based_on_gpt2",
-    "alibidaran/medical_transcription_generator",
-    "Deci/DeciCoder-1b",
-    "microsoft/DialoGPT-medium",
-    "ogimgio/gpt-neo-125m-neurallinguisticpioneers",
-    "open-llm-leaderboard/bloom-560m-4bit-alpaca-auto-eval-adapter-applied",
-    "BreadAi/gpt-YA-1-1_160M",
-    "microsoft/DialoGPT-large",
-    "facebook/opt-125m",
-    "huggingtweets/jerma985",
-    "Locutusque/gpt2-conversational-or-qa",
-    "concedo/Pythia-70M-ChatSalad",
-    "roneneldan/TinyStories-1M",
-    "BreadAi/DiscordPy",
-    "bigcode/gpt_bigcode-santacoder",
-    "Tincando/fiction_story_generator",
-    "klosax/pythia-70m-deduped-step44k-92bt",
-    "Quake24/easyTermsSummerizer",
-    "BreadAi/gpt-YA-1-1_70M",
-    "EleutherAI/pythia-160m",
-    "euclaise/gpt-neox-122m-minipile-digits",
-    "MBZUAI/lamini-cerebras-590m",
-    "nicholasKluge/Aira-124M",
-    "MayaPH/FinOPT-Washington",
-    "cyberagent/open-calm-large",
-    "BreadAi/StoryPy",
-    "EleutherAI/pythia-70m",
-    "BreadAi/gpt-Youtube",
-    "roneneldan/TinyStories-33M",
-    "EleutherAI/pythia-70m-deduped",
-    "lgaalves/gpt2_guanaco-dolly-platypus",
-    "Corianas/Quokka_590m",
-    "lgaalves/gpt2_platypus-dolly-guanaco",
-    "cyberagent/open-calm-7b",
-    "RWKV/rwkv-4-169m-pile",
-    "gpt2",
-    "roneneldan/TinyStories-28M",
-    "lgaalves/gpt2_open-platypus",
-    "gpt2",
-    "SaylorTwift/gpt2_test",
-    "roneneldan/TinyStories-3M",
-    "nthngdy/pythia-owt2-70m-50k",
-    "Corianas/256_5epoch",
-    "roneneldan/TinyStories-8M",
-    "lgaalves/gpt2-dolly",
-    "nthngdy/pythia-owt2-70m-100k",
-    "aisquared/dlite-v2-124m",
-    "mncai/SGPT-1.3B-insurance-epoch10",
-    "huggingtweets/gladosystem",
-    "abhiramtirumala/DialoGPT-sarcastic-medium",
-    "MBZUAI/lamini-cerebras-256m",
-    "cerebras/Cerebras-GPT-111M",
-    "uberkie/metharme-1.3b-finetuned",
-    "MBZUAI/lamini-cerebras-111m",
-    "psyche/kogpt",
-    "Corianas/Quokka_256m",
-    "vicgalle/gpt2-alpaca-gpt4",
-    "aisquared/dlite-v1-124m",
-    "Mikivis/xuanxuan",
-    "MBZUAI/LaMini-GPT-124M",
-    "vicgalle/gpt2-alpaca",
-    "huashiyiqike/testmodel",
-    "Corianas/111m",
-    "baseline",
-]

src/tools/plots.py

@@ -1,154 +0,0 @@
-import pandas as pd
-import numpy as np
-import plotly.express as px
-from plotly.graph_objs import Figure
-
-from src.leaderboard.filter_models import FLAGGED_MODELS
-from src.display.utils import human_baseline_row as HUMAN_BASELINE, AutoEvalColumn, Tasks, Task, BENCHMARK_COLS
-from src.leaderboard.read_evals import EvalResult
-
-
-
-def create_scores_df(raw_data: list[EvalResult]) -> pd.DataFrame:
-    """
-    Generates a DataFrame containing the maximum scores until each date.
-
-    :param results_df: A DataFrame containing result information including metric scores and dates.
-    :return: A new DataFrame containing the maximum scores until each date for every metric.
-    """
-    # Step 1: Ensure 'date' is in datetime format and sort the DataFrame by it
-    results_df = pd.DataFrame(raw_data)
-    #results_df["date"] = pd.to_datetime(results_df["date"], format="mixed", utc=True)
-    results_df.sort_values(by="date", inplace=True)
-
-    # Step 2: Initialize the scores dictionary
-    scores = {k: [] for k in BENCHMARK_COLS + [AutoEvalColumn.average.name]}
-
-    # Step 3: Iterate over the rows of the DataFrame and update the scores dictionary
-    for task in [t.value for t in Tasks] + [Task("Average", "avg", AutoEvalColumn.average.name)]:
-        current_max = 0
-        last_date = ""
-        column = task.col_name
-        for _, row in results_df.iterrows():
-            current_model = row["full_model"]
-            if current_model in FLAGGED_MODELS:
-                continue
-
-            current_date = row["date"]
-            if task.benchmark == "Average":
-                current_score = np.mean(list(row["results"].values()))
-            else:
-                current_score = row["results"][task.benchmark]
-
-            if current_score > current_max:
-                if current_date == last_date and len(scores[column]) > 0:
-                    scores[column][-1] = {"model": current_model, "date": current_date, "score": current_score}
-                else:
-                    scores[column].append({"model": current_model, "date": current_date, "score": current_score})
-                current_max = current_score
-                last_date = current_date
-
-    # Step 4: Return all dictionaries as DataFrames
-    return {k: pd.DataFrame(v) for k, v in scores.items()}
-
-
-def create_plot_df(scores_df: dict[str: pd.DataFrame]) -> pd.DataFrame:
-    """
-    Transforms the scores DataFrame into a new format suitable for plotting.
-
-    :param scores_df: A DataFrame containing metric scores and dates.
-    :return: A new DataFrame reshaped for plotting purposes.
-    """
-    # Initialize the list to store DataFrames
-    dfs = []
-
-    # Iterate over the cols and create a new DataFrame for each column
-    for col in BENCHMARK_COLS + [AutoEvalColumn.average.name]:
-        d = scores_df[col].reset_index(drop=True)
-        d["task"] = col
-        dfs.append(d)
-
-    # Concatenate all the created DataFrames
-    concat_df = pd.concat(dfs, ignore_index=True)
-
-    # Sort values by 'date'
-    concat_df.sort_values(by="date", inplace=True)
-    concat_df.reset_index(drop=True, inplace=True)
-    return concat_df
-
-
-def create_metric_plot_obj(
-    df: pd.DataFrame, metrics: list[str], title: str
-) -> Figure:
-    """
-    Create a Plotly figure object with lines representing different metrics
-    and horizontal dotted lines representing human baselines.
-
-    :param df: The DataFrame containing the metric values, names, and dates.
-    :param metrics: A list of strings representing the names of the metrics
-                    to be included in the plot.
-    :param title: A string representing the title of the plot.
-    :return: A Plotly figure object with lines representing metrics and
-             horizontal dotted lines representing human baselines.
-    """
-
-    # Filter the DataFrame based on the specified metrics
-    df = df[df["task"].isin(metrics)]
-
-    # Filter the human baselines based on the specified metrics
-    filtered_human_baselines = {k: v for k, v in HUMAN_BASELINE.items() if k in metrics}
-
-    # Create a line figure using plotly express with specified markers and custom data
-    fig = px.line(
-        df,
-        x="date",
-        y="score",
-        color="task",
-        markers=True,
-        custom_data=["task", "score", "model"],
-        title=title,
-    )
-
-    # Update hovertemplate for better hover interaction experience
-    fig.update_traces(
-        hovertemplate="<br>".join(
-            [
-                "Model Name: %{customdata[2]}",
-                "Metric Name: %{customdata[0]}",
-                "Date: %{x}",
-                "Metric Value: %{y}",
-            ]
-        )
-    )
-
-    # Update the range of the y-axis
-    fig.update_layout(yaxis_range=[0, 100])
-
-    # Create a dictionary to hold the color mapping for each metric
-    metric_color_mapping = {}
-
-    # Map each metric name to its color in the figure
-    for trace in fig.data:
-        metric_color_mapping[trace.name] = trace.line.color
-
-    # Iterate over filtered human baselines and add horizontal lines to the figure
-    for metric, value in filtered_human_baselines.items():
-        color = metric_color_mapping.get(metric, "blue")  # Retrieve color from mapping; default to blue if not found
-        location = "top left" if metric == "HellaSwag" else "bottom left"  # Set annotation position
-        # Add horizontal line with matched color and positioned annotation
-        fig.add_hline(
-            y=value,
-            line_dash="dot",
-            annotation_text=f"{metric} human baseline",
-            annotation_position=location,
-            annotation_font_size=10,
-            annotation_font_color=color,
-            line_color=color,
-        )
-
-    return fig
-
-
-# Example Usage:
-# human_baselines dictionary is defined.
-# chart = create_metric_plot_obj(scores_df, ["ARC", "HellaSwag", "MMLU", "TruthfulQA"], human_baselines, "Graph Title")