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README.md
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README.md
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---
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language:
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- en
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license: apache-2.0
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datasets:
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- allenai/olmOCR-mix-0225
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base_model:
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- Qwen/Qwen2-VL-7B-Instruct
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library_name: transformers
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---
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<img alt="olmOCR Logo" src="https://huggingface.co/datasets/allenai/blog-images/resolve/main/olmocr/olmocr.png" width="242px" style="margin-left:'auto' margin-right:'auto' display:'block'">
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# olmOCR-7B-0225-preview
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olmOCR-7B-0225-preview
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This is a preview release of the olmOCR model that's fine tuned from Qwen2-VL-7B-Instruct using the
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[olmOCR-mix-0225](https://huggingface.co/datasets/allenai/olmOCR-mix-0225) dataset.
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Quick links:
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- 📃 [Paper](https://olmocr.allenai.org/papers/olmocr.pdf)
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- 🤗 [Dataset](https://huggingface.co/datasets/allenai/olmOCR-mix-0225)
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- 🛠️ [Code](https://github.com/allenai/olmocr)
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- 🎮 [Demo](https://olmocr.allenai.org/)
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The best way to use this model is via the [olmOCR toolkit](https://github.com/allenai/olmocr).
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The toolkit comes with an efficient inference setup via sglang that can handle millions of documents
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at scale.
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## Usage
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This model expects as input a single document image, rendered such that the longest dimension is 1024 pixels.
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The prompt must then contain the additional metadata from the document, and the easiest way to generate this
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is to use the methods provided by the [olmOCR toolkit](https://github.com/allenai/olmocr).
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## Manual Prompting
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If you want to prompt this model manually instead of using the [olmOCR toolkit](https://github.com/allenai/olmocr), please see the code below.
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In normal usage, the olmOCR toolkit builds the prompt by rendering the PDF page, and
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extracting relevant text blocks and image metadata. To duplicate that you will need to
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```bash
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pip install olmocr
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```
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and then run the following sample code.
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```python
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import torch
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import base64
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import urllib.request
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from io import BytesIO
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from PIL import Image
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from transformers import AutoProcessor, Qwen2VLForConditionalGeneration
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from olmocr.data.renderpdf import render_pdf_to_base64png
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from olmocr.prompts import build_finetuning_prompt
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from olmocr.prompts.anchor import get_anchor_text
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# Initialize the model
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model = Qwen2VLForConditionalGeneration.from_pretrained("allenai/olmOCR-7B-0225-preview", torch_dtype=torch.bfloat16).eval()
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processor = AutoProcessor.from_pretrained("Qwen/Qwen2-VL-7B-Instruct")
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device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
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model.to(device)
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# Grab a sample PDF
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urllib.request.urlretrieve("https://molmo.allenai.org/paper.pdf", "./paper.pdf")
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# Render page 1 to an image
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image_base64 = render_pdf_to_base64png("./paper.pdf", 1, target_longest_image_dim=1024)
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# Build the prompt, using document metadata
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anchor_text = get_anchor_text("./paper.pdf", 1, pdf_engine="pdfreport", target_length=4000)
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prompt = build_finetuning_prompt(anchor_text)
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# Build the full prompt
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messages = [
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{
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"role": "user",
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"content": [
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{"type": "text", "text": prompt},
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{"type": "image_url", "image_url": {"url": f"data:image/png;base64,{image_base64}"}},
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],
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}
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]
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# Apply the chat template and processor
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text = processor.apply_chat_template(messages, tokenize=False, add_generation_prompt=True)
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main_image = Image.open(BytesIO(base64.b64decode(image_base64)))
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inputs = processor(
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text=[text],
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images=[main_image],
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padding=True,
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return_tensors="pt",
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)
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inputs = {key: value.to(device) for (key, value) in inputs.items()}
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# Generate the output
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output = model.generate(
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**inputs,
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temperature=0.8,
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max_new_tokens=50,
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num_return_sequences=1,
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do_sample=True,
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)
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# Decode the output
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prompt_length = inputs["input_ids"].shape[1]
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new_tokens = output[:, prompt_length:]
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text_output = processor.tokenizer.batch_decode(
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new_tokens, skip_special_tokens=True
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)
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print(text_output)
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# ['{"primary_language":"en","is_rotation_valid":true,"rotation_correction":0,"is_table":false,"is_diagram":false,"natural_text":"Molmo and PixMo:\\nOpen Weights and Open Data\\nfor State-of-the']
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```
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## License and use
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olmOCR is licensed under the Apache 2.0 license.
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olmOCR is intended for research and educational use.
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For more information, please see our [Responsible Use Guidelines](https://allenai.org/responsible-use).
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{
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"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}"
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}
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{
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"architectures": [
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"Qwen2VLForConditionalGeneration"
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],
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"attention_dropout": 0.0,
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"bos_token_id": 151643,
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"eos_token_id": 151645,
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"vision_start_token_id": 151652,
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"vision_end_token_id": 151653,
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"vision_token_id": 151654,
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"image_token_id": 151655,
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"video_token_id": 151656,
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"hidden_act": "silu",
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"hidden_size": 3584,
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"initializer_range": 0.02,
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"intermediate_size": 18944,
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"max_position_embeddings": 32768,
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"max_window_layers": 28,
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"model_type": "qwen2_vl",
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"num_attention_heads": 28,
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"num_hidden_layers": 28,
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"num_key_value_heads": 4,
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"rms_norm_eps": 1e-06,
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"rope_theta": 1000000.0,
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"sliding_window": 32768,
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"tie_word_embeddings": false,
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"torch_dtype": "bfloat16",
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"transformers_version": "4.41.2",
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"use_cache": true,
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"use_sliding_window": false,
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"vision_config": {
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"depth": 32,
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"embed_dim": 1280,
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"mlp_ratio": 4,
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"num_heads": 16,
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"in_chans": 3,
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"hidden_size": 3584,
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"patch_size": 14,
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"spatial_merge_size": 2,
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"spatial_patch_size": 14,
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"temporal_patch_size": 2
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},
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"rope_scaling": {
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"type": "mrope",
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"mrope_section": [
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16,
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24,
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24
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]
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},
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"vocab_size": 152064
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}
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{
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"bos_token_id": 151643,
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"pad_token_id": 151643,
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"do_sample": true,
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"eos_token_id": [
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151645,
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151643
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],
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"repetition_penalty": 1.0,
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"temperature": 0.01,
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"top_p": 0.001,
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"top_k": 1,
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"transformers_version": "4.37.0"
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}
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{
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"visual.blocks.9.mlp.fc2.bias": "model-00001-of-00004.safetensors",
|
||||
"visual.blocks.9.mlp.fc2.weight": "model-00001-of-00004.safetensors",
|
||||
"visual.blocks.9.norm1.bias": "model-00001-of-00004.safetensors",
|
||||
"visual.blocks.9.norm1.weight": "model-00001-of-00004.safetensors",
|
||||
"visual.blocks.9.norm2.bias": "model-00001-of-00004.safetensors",
|
||||
"visual.blocks.9.norm2.weight": "model-00001-of-00004.safetensors",
|
||||
"visual.merger.ln_q.bias": "model-00001-of-00004.safetensors",
|
||||
"visual.merger.ln_q.weight": "model-00001-of-00004.safetensors",
|
||||
"visual.merger.mlp.0.bias": "model-00001-of-00004.safetensors",
|
||||
"visual.merger.mlp.0.weight": "model-00001-of-00004.safetensors",
|
||||
"visual.merger.mlp.2.bias": "model-00001-of-00004.safetensors",
|
||||
"visual.merger.mlp.2.weight": "model-00001-of-00004.safetensors",
|
||||
"visual.patch_embed.proj.weight": "model-00001-of-00004.safetensors"
|
||||
}
|
||||
}
|
||||
|
|
@ -0,0 +1,19 @@
|
|||
{
|
||||
"min_pixels": 3136,
|
||||
"max_pixels": 12845056,
|
||||
"patch_size": 14,
|
||||
"temporal_patch_size": 2,
|
||||
"merge_size": 2,
|
||||
"image_mean": [
|
||||
0.48145466,
|
||||
0.4578275,
|
||||
0.40821073
|
||||
],
|
||||
"image_std": [
|
||||
0.26862954,
|
||||
0.26130258,
|
||||
0.27577711
|
||||
],
|
||||
"image_processor_type": "Qwen2VLImageProcessor",
|
||||
"processor_class": "Qwen2VLProcessor"
|
||||
}
|
||||
File diff suppressed because it is too large
Load Diff
|
|
@ -0,0 +1,129 @@
|
|||
{
|
||||
"add_prefix_space": false,
|
||||
"added_tokens_decoder": {
|
||||
"151643": {
|
||||
"content": "<|endoftext|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151644": {
|
||||
"content": "<|im_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151645": {
|
||||
"content": "<|im_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151646": {
|
||||
"content": "<|object_ref_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151647": {
|
||||
"content": "<|object_ref_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151648": {
|
||||
"content": "<|box_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151649": {
|
||||
"content": "<|box_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151650": {
|
||||
"content": "<|quad_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151651": {
|
||||
"content": "<|quad_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151652": {
|
||||
"content": "<|vision_start|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151653": {
|
||||
"content": "<|vision_end|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151654": {
|
||||
"content": "<|vision_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151655": {
|
||||
"content": "<|image_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
},
|
||||
"151656": {
|
||||
"content": "<|video_pad|>",
|
||||
"lstrip": false,
|
||||
"normalized": false,
|
||||
"rstrip": false,
|
||||
"single_word": false,
|
||||
"special": true
|
||||
}
|
||||
},
|
||||
"additional_special_tokens": ["<|im_start|>", "<|im_end|>", "<|object_ref_start|>","<|object_ref_end|>","<|box_start|>","<|box_end|>","<|quad_start|>","<|quad_end|>","<|vision_start|>","<|vision_end|>","<|vision_pad|>","<|image_pad|>","<|video_pad|>"],
|
||||
"bos_token": null,
|
||||
"chat_template": "{% set image_count = namespace(value=0) %}{% set video_count = namespace(value=0) %}{% for message in messages %}{% if loop.first and message['role'] != 'system' %}<|im_start|>system\nYou are a helpful assistant.<|im_end|>\n{% endif %}<|im_start|>{{ message['role'] }}\n{% if message['content'] is string %}{{ message['content'] }}<|im_end|>\n{% else %}{% for content in message['content'] %}{% if content['type'] == 'image' or 'image' in content or 'image_url' in content %}{% set image_count.value = image_count.value + 1 %}{% if add_vision_id %}Picture {{ image_count.value }}: {% endif %}<|vision_start|><|image_pad|><|vision_end|>{% elif content['type'] == 'video' or 'video' in content %}{% set video_count.value = video_count.value + 1 %}{% if add_vision_id %}Video {{ video_count.value }}: {% endif %}<|vision_start|><|video_pad|><|vision_end|>{% elif 'text' in content %}{{ content['text'] }}{% endif %}{% endfor %}<|im_end|>\n{% endif %}{% endfor %}{% if add_generation_prompt %}<|im_start|>assistant\n{% endif %}",
|
||||
"clean_up_tokenization_spaces": false,
|
||||
"eos_token": "<|im_end|>",
|
||||
"padding_side": "left",
|
||||
"errors": "replace",
|
||||
"model_max_length": 32768,
|
||||
"pad_token": "<|endoftext|>",
|
||||
"split_special_tokens": false,
|
||||
"tokenizer_class": "Qwen2Tokenizer",
|
||||
"unk_token": null
|
||||
}
|
||||
File diff suppressed because one or more lines are too long
Loading…
Reference in New Issue