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README.md
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README.md
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---
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license: Apache License 2.0
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tags: []
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#model-type:
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##如 gpt、phi、llama、chatglm、baichuan 等
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#- gpt
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#domain:
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##如 nlp、cv、audio、multi-modal
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#- nlp
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#language:
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##语言代码列表 https://help.aliyun.com/document_detail/215387.html?spm=a2c4g.11186623.0.0.9f8d7467kni6Aa
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#- cn
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#metrics:
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##如 CIDEr、Blue、ROUGE 等
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#- CIDEr
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#tags:
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##各种自定义,包括 pretrained、fine-tuned、instruction-tuned、RL-tuned 等训练方法和其他
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#- pretrained
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#tools:
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##如 vllm、fastchat、llamacpp、AdaSeq 等
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#- vllm
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pipeline_tag: image-text-to-text
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language:
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- multilingual
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tags:
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- deepseek
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- vision-language
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- ocr
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- custom_code
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license: mit
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---
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### 当前模型的贡献者未提供更加详细的模型介绍。模型文件和权重,可浏览“模型文件”页面获取。
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#### 您可以通过如下git clone命令,或者ModelScope SDK来下载模型
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<div align="center">
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<img src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/logo.svg?raw=true" width="60%" alt="DeepSeek AI" />
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</div>
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<hr>
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<div align="center">
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<a href="https://www.deepseek.com/" target="_blank">
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<img alt="Homepage" src="https://github.com/deepseek-ai/DeepSeek-V2/blob/main/figures/badge.svg?raw=true" />
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</a>
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<a href="https://huggingface.co/deepseek-ai/DeepSeek-OCR" target="_blank">
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<img alt="Hugging Face" src="https://img.shields.io/badge/%F0%9F%A4%97%20Hugging%20Face-DeepSeek%20AI-ffc107?color=ffc107&logoColor=white" />
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</a>
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</div>
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<div align="center">
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<a href="https://discord.gg/Tc7c45Zzu5" target="_blank">
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<img alt="Discord" src="https://img.shields.io/badge/Discord-DeepSeek%20AI-7289da?logo=discord&logoColor=white&color=7289da" />
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</a>
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<a href="https://twitter.com/deepseek_ai" target="_blank">
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<img alt="Twitter Follow" src="https://img.shields.io/badge/Twitter-deepseek_ai-white?logo=x&logoColor=white" />
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</a>
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</div>
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<p align="center">
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<a href="https://github.com/deepseek-ai/DeepSeek-OCR"><b>🌟 Github</b></a> |
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<a href="https://huggingface.co/deepseek-ai/DeepSeek-OCR"><b>📥 Model Download</b></a> |
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<a href="https://github.com/deepseek-ai/DeepSeek-OCR/blob/main/DeepSeek_OCR_paper.pdf"><b>📄 Paper Link</b></a> |
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<a href=""><b>📄 Arxiv Paper Link</b></a> |
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</p>
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<h2>
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<p align="center">
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<a href="">DeepSeek-OCR: Contexts Optical Compression</a>
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</p>
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</h2>
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<p align="center">
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<img src="assets/fig1.png" style="width: 1000px" align=center>
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</p>
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<p align="center">
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<a href="">Explore the boundaries of visual-text compression.</a>
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</p>
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## Usage
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Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.12.9 + CUDA11.8:
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SDK下载
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```bash
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#安装ModelScope
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pip install modelscope
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```
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torch==2.6.0
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transformers==4.46.3
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tokenizers==0.20.3
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einops
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addict
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easydict
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pip install flash-attn==2.7.3 --no-build-isolation
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```
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```python
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#SDK模型下载
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from modelscope import snapshot_download
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model_dir = snapshot_download('deepseek-ai/DeepSeek-OCR')
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```
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Git下载
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```
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#Git模型下载
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git clone https://www.modelscope.cn/deepseek-ai/DeepSeek-OCR.git
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from transformers import AutoModel, AutoTokenizer
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import torch
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import os
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os.environ["CUDA_VISIBLE_DEVICES"] = '0'
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model_name = 'deepseek-ai/DeepSeek-OCR'
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tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)
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model = AutoModel.from_pretrained(model_name, _attn_implementation='flash_attention_2', trust_remote_code=True, use_safetensors=True)
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model = model.eval().cuda().to(torch.bfloat16)
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# prompt = "<image>\nFree OCR. "
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prompt = "<image>\n<|grounding|>Convert the document to markdown. "
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image_file = 'your_image.jpg'
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output_path = 'your/output/dir'
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# infer(self, tokenizer, prompt='', image_file='', output_path = ' ', base_size = 1024, image_size = 640, crop_mode = True, test_compress = False, save_results = False):
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# Tiny: base_size = 512, image_size = 512, crop_mode = False
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# Small: base_size = 640, image_size = 640, crop_mode = False
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# Base: base_size = 1024, image_size = 1024, crop_mode = False
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# Large: base_size = 1280, image_size = 1280, crop_mode = False
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# Gundam: base_size = 1024, image_size = 640, crop_mode = True
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res = model.infer(tokenizer, prompt=prompt, image_file=image_file, output_path = output_path, base_size = 1024, image_size = 640, crop_mode=True, save_results = True, test_compress = True)
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```
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<p style="color: lightgrey;">如果您是本模型的贡献者,我们邀请您根据<a href="https://modelscope.cn/docs/ModelScope%E6%A8%A1%E5%9E%8B%E6%8E%A5%E5%85%A5%E6%B5%81%E7%A8%8B%E6%A6%82%E8%A7%88" style="color: lightgrey; text-decoration: underline;">模型贡献文档</a>,及时完善模型卡片内容。</p>
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## vLLM
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Refer to [🌟GitHub](https://github.com/deepseek-ai/DeepSeek-OCR/) for guidance on model inference acceleration and PDF processing, etc.<!-- -->
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## Visualizations
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<table>
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<tr>
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<td><img src="assets/show1.jpg" style="width: 500px"></td>
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<td><img src="assets/show2.jpg" style="width: 500px"></td>
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</tr>
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<tr>
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<td><img src="assets/show3.jpg" style="width: 500px"></td>
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<td><img src="assets/show4.jpg" style="width: 500px"></td>
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</tr>
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</table>
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## Acknowledgement
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We would like to thank [Vary](https://github.com/Ucas-HaoranWei/Vary/), [GOT-OCR2.0](https://github.com/Ucas-HaoranWei/GOT-OCR2.0/), [MinerU](https://github.com/opendatalab/MinerU), [PaddleOCR](https://github.com/PaddlePaddle/PaddleOCR), [OneChart](https://github.com/LingyvKong/OneChart), [Slow Perception](https://github.com/Ucas-HaoranWei/Slow-Perception) for their valuable models and ideas.
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We also appreciate the benchmarks: [Fox](https://github.com/ucaslcl/Fox), [OminiDocBench](https://github.com/opendatalab/OmniDocBench).
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## Citation
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Coming soon!
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