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README.md

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 ---
-license: gpl-3.0
+license: mit
+datasets:
+- liuhaotian/LLaVA-Pretrain
+- liuhaotian/LLaVA-Instruct-150K
+language:
+- en
+- zh
+library_name: transformers
 ---
+
+# WORK IN PROGRESS
+We present TinyLLaVA, a small vision-language chatbot (1.4B) that reaches comparable performances with contemporary vision language models on common benchmarks, using less parameters.
+TinyLLaVA was trained by finetuning [TinyLlama](https://huggingface.co/PY007/TinyLlama-1.1B-Chat-v0.3) on the [LLaVA-1.5](https://github.com/haotian-liu/LLaVA) dataset, following the training recipe of [LLaVA-1.5](https://github.com/haotian-liu/LLaVA). For more details, please refer to the [LLaVA-1.5 paper](https://arxiv.org/abs/2310.03744).
+
+
+## Model Performance
+We have evaluated TinyLLaVA on [GQA](https://cs.stanford.edu/people/dorarad/gqa/about.html), [VizWiz](https://www.vizwiz.com/), [VQAv2](https://visualqa.org/), [TextVQA](https://textvqa.org/) and [SQA](https://github.com/lupantech/ScienceQA).
+
+|   Model   |     VQAv2      |      GQA       |       SQA      |      TextVQA   |      VizWiz    |
+| -------------------- | :------------: | :------------: | :------------: | :------------: | :------------: |
+|   TinyLLaVA-v1-1.4B  |      73.41     |     57.54      |     59.40      |     46.37      |      49.56      |
+|   BLIP-2             |      41.00     |     41.00      |     61.00      |     42.50      |      19.60      |
+|   LLaVA-v1.5-7B      |      78.50     |     62.00      |     66.80      |     61.3      |      50      |
+|   LLaVA-v1.5-13B     |      80.00     |     63.30      |     71.60      |     61.3      |      53.6      |
+|   Qwen-VL-7B         |      78.80     |     59.30      |     67.10      |     63.8      |      35.2      |
+|   Qwen-VL-13B        |      78.20     |     57.50      |     68.20      |     61.5      |      38.9      |
+
+
+
+More evaluations are ongoing.
+
+
+## Model Preparations
+
+#### - Transformers Version
+Make sure to have `transformers >= 4.35.3`.
+
+#### - Prompt Template
+The model supports multi-image and multi-prompt generation. When using the model, make sure to follow the correct prompt template (`USER: <image>xxx\nASSISTANT:`), where `<image>` token is a place-holding special token for image embeddings.
+
+## Model Inference from `pipeline` and `transformers`
+#### - Using `pipeline`:
+Below we used [`"bczhou/tiny-llava-v1-hf"`](https://huggingface.co/bczhou/tiny-llava-v1-hf) checkpoint.
+
+```python
+from transformers import pipeline
+from PIL import Image
+import requests
+model_id = "bczhou/tiny-llava-v1-hf"
+pipe = pipeline("image-to-text", model=model_id)
+url = "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/transformers/tasks/ai2d-demo.jpg"
+image = Image.open(requests.get(url, stream=True).raw)
+prompt = "USER: <image>\nWhat does the label 15 represent? (1) lava (2) core (3) tunnel (4) ash cloud\nASSISTANT:"
+outputs = pipe(image, prompt=prompt, generate_kwargs={"max_new_tokens": 200})
+print(outputs[0])
+>>> {"generated_text': 'USER:  \nWhat does the label 15 represent? (1) lava (2) core (3) tunnel (4) ash cloud\nASSISTANT: The label 15 represents lava, which is a type of volcanic rock."}
+```
+
+#### - Using pure `transformers`:
+Below is an example script to run generation in `float16` precision on a GPU device:
+
+```python
+import requests
+from PIL import Image
+import torch
+from transformers import AutoProcessor, LlavaForConditionalGeneration
+model_id = "bczhou/tiny-llava-v1-hf"
+prompt = "USER: <image>\nWhat are these?\nASSISTANT:"
+image_file = "http://images.cocodataset.org/val2017/000000039769.jpg"
+model = LlavaForConditionalGeneration.from_pretrained(
+model_id,
+torch_dtype=torch.float16,
+low_cpu_mem_usage=True,
+).to(0)
+processor = AutoProcessor.from_pretrained(model_id)
+raw_image = Image.open(requests.get(image_file, stream=True).raw)
+inputs = processor(prompt, raw_image, return_tensors='pt').to(0, torch.float16)
+output = model.generate(**inputs, max_new_tokens=200, do_sample=False)
+print(processor.decode(output[0][2:], skip_special_tokens=True))
+```
+
+## Contact
+This model was trained by [Baichuan Zhou](https://baichuanzhou.github.io/), from Beihang Univerisity, under the supervision of  [Prof. Lei Huang](https://huangleibuaa.github.io/).

config.json

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+{
+  "architectures": [
+    "LlavaForConditionalGeneration"
+  ],
+  "ignore_index": -100,
+  "image_token_index": 32000,
+  "model_type": "llava",
+  "pad_token_id": 32001,
+  "projector_hidden_act": "gelu",
+  "text_config": {
+    "_name_or_path": "TinyLlama/TinyLlama-1.1B-Chat-v1.0",
+    "architectures": [
+      "LlamaForCausalLM"
+    ],
+    "hidden_size": 2048,
+    "intermediate_size": 5632,
+    "model_type": "llama",
+    "num_hidden_layers": 22,
+    "num_key_value_heads": 4,
+    "rms_norm_eps": 1e-05,
+    "torch_dtype": "bfloat16",
+    "vocab_size": 32064
+  },
+  "torch_dtype": "float32",
+  "transformers_version": "4.36.2",
+  "vision_config": {
+    "hidden_size": 1024,
+    "image_size": 336,
+    "intermediate_size": 4096,
+    "model_type": "clip_vision_model",
+    "num_attention_heads": 16,
+    "num_hidden_layers": 24,
+    "patch_size": 14,
+    "projection_dim": 768,
+    "vocab_size": 32000
+  },
+  "vision_feature_layer": -2,
+  "vision_feature_select_strategy": "default",
+  "vocab_size": 32064
+}

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 1,
+  "eos_token_id": 2,
+  "pad_token_id": 32001,
+  "transformers_version": "4.36.2"
+}

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preprocessor_config.json

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+{
+  "crop_size": {
+    "height": 336,
+    "width": 336
+  },
+  "do_center_crop": true,
+  "do_convert_rgb": true,
+  "do_normalize": true,
+  "do_rescale": true,
+  "do_resize": true,
+  "feature_extractor_type": "CLIPFeatureExtractor",
+  "image_mean": [
+    0.48145466,
+    0.4578275,
+    0.40821073
+  ],
+  "image_processor_type": "CLIPImageProcessor",
+  "image_std": [
+    0.26862954,
+    0.26130258,
+    0.27577711
+  ],
+  "processor_class": "LlavaProcessor",
+  "resample": 3,
+  "rescale_factor": 0.00392156862745098,
+  "size": {
+    "shortest_edge": 336
+  }
+}

special_tokens_map.json

@@ -0,0 +1,30 @@
+{
+  "bos_token": {
+    "content": "<s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "eos_token": {
+    "content": "</s>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "pad_token": {
+    "content": "<pad>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  },
+  "unk_token": {
+    "content": "<unk>",
+    "lstrip": false,
+    "normalized": false,
+    "rstrip": false,
+    "single_word": false
+  }
+}

tokenizer_config.json

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+{
+  "add_bos_token": true,
+  "add_eos_token": false,
+  "added_tokens_decoder": {
+    "0": {
+      "content": "<unk>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "1": {
+      "content": "<s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "2": {
+      "content": "</s>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32000": {
+      "content": "<image>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    },
+    "32001": {
+      "content": "<pad>",
+      "lstrip": false,
+      "normalized": false,
+      "rstrip": false,
+      "single_word": false,
+      "special": true
+    }
+  },
+  "bos_token": "<s>",
+  "chat_template": "{% for message in messages %}\n{% if message['role'] == 'user' %}\n{{ '<|user|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'system' %}\n{{ '<|system|>\n' + message['content'] + eos_token }}\n{% elif message['role'] == 'assistant' %}\n{{ '<|assistant|>\n'  + message['content'] + eos_token }}\n{% endif %}\n{% if loop.last and add_generation_prompt %}\n{{ '<|assistant|>' }}\n{% endif %}\n{% endfor %}",
+  "clean_up_tokenization_spaces": false,
+  "eos_token": "</s>",
+  "legacy": false,
+  "model_max_length": 2048,
+  "pad_token": "<pad>",
+  "padding_side": "right",
+  "processor_class": "LlavaProcessor",
+  "sp_model_kwargs": {},
+  "tokenizer_class": "LlamaTokenizer",
+  "unk_token": "<unk>",
+  "use_default_system_prompt": false
+}