deepseek-ai/DeepSeek-OCR-2

image-text-to-texttransformersUpstream checksumstransformerssafetensorsdeepseek_vl_v2feature-extractiondeepseekvision-language

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DeepSeek-OCR 2: Visual Causal Flow [blocked]

[Image blocked: No description]

Explore more human-like visual encoding. [blocked]

Usage

Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.12.9 + CUDA11.8：

python

from transformers import AutoModel, AutoTokenizerimport torchimport osos.environ["CUDA_VISIBLE_DEVICES"] = '0'model_name = 'deepseek-ai/DeepSeek-OCR-2'
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)model = AutoModel.from_pretrained(model_name, _attn_implementation='flash_attention_2', trust_remote_code=True, use_safetensors=True)model = model.eval().cuda().to(torch.bfloat16)
# prompt = "<image>\nFree OCR. "prompt = "<image>\n<|grounding|>Convert the document to markdown. "image_file = 'your_image.jpg'output_path = 'your/output/dir'

res = model.infer(tokenizer, prompt=prompt, image_file=image_file, output_path = output_path, base_size = 1024, image_size = 768, crop_mode=True, save_results = True)

vLLM

Refer to 🌟GitHub for guidance on model inference acceleration and PDF processing, etc.

Support-Modes

Dynamic resolution
- Default: (0-6)×768×768 + 1×1024×1024 — (0-6)×144 + 256 visual tokens ✅

Main Prompts

Acknowledgement

We would like to thank DeepSeek-OCR, Vary, GOT-OCR2.0, MinerU, PaddleOCR for their valuable models and ideas.

We also appreciate the benchmark OmniDocBench.

Citation

bibtex

@article{wei2025deepseek,  title={DeepSeek-OCR: Contexts Optical Compression},  author={Wei, Haoran and Sun, Yaofeng and Li, Yukun},  journal={arXiv preprint arXiv:2510.18234},  year={2025}}@article{wei2026deepseek,  title={DeepSeek-OCR 2: Visual Causal Flow},  author={Wei, Haoran and Sun, Yaofeng and Li, Yukun},  journal={arXiv preprint arXiv:2601.20552},  year={2026}}

Usage

Inference using Huggingface transformers on NVIDIA GPUs. Requirements tested on python 3.12.9 + CUDA11.8：

python

from transformers import AutoModel, AutoTokenizerimport torchimport osos.environ["CUDA_VISIBLE_DEVICES"] = '0'model_name = 'deepseek-ai/DeepSeek-OCR-2'
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)model = AutoModel.from_pretrained(model_name, _attn_implementation='flash_attention_2', trust_remote_code=True, use_safetensors=True)model = model.eval().cuda().to(torch.bfloat16)
# prompt = "<image>\nFree OCR. "prompt = "<image>\n<|grounding|>Convert the document to markdown. "image_file = 'your_image.jpg'output_path = 'your/output/dir'

res = model.infer(tokenizer, prompt=prompt, image_file=image_file, output_path = output_path, base_size = 1024, image_size = 768, crop_mode=True, save_results = True)

from transformers import AutoModel, AutoTokenizerimport torchimport osos.environ["CUDA_VISIBLE_DEVICES"] = '0'model_name = 'deepseek-ai/DeepSeek-OCR-2'
tokenizer = AutoTokenizer.from_pretrained(model_name, trust_remote_code=True)model = AutoModel.from_pretrained(model_name, _attn_implementation='flash_attention_2', trust_remote_code=True, use_safetensors=True)model = model.eval().cuda().to(torch.bfloat16)
# prompt = "<image>\nFree OCR. "prompt = "<image>\n<|grounding|>Convert the document to markdown. "image_file = 'your_image.jpg'output_path = 'your/output/dir'

res = model.infer(tokenizer, prompt=prompt, image_file=image_file, output_path = output_path, base_size = 1024, image_size = 768, crop_mode=True, save_results = True)

Citation

bibtex

@article{wei2025deepseek,  title={DeepSeek-OCR: Contexts Optical Compression},  author={Wei, Haoran and Sun, Yaofeng and Li, Yukun},  journal={arXiv preprint arXiv:2510.18234},  year={2025}}@article{wei2026deepseek,  title={DeepSeek-OCR 2: Visual Causal Flow},  author={Wei, Haoran and Sun, Yaofeng and Li, Yukun},  journal={arXiv preprint arXiv:2601.20552},  year={2026}}

@article{wei2025deepseek,  title={DeepSeek-OCR: Contexts Optical Compression},  author={Wei, Haoran and Sun, Yaofeng and Li, Yukun},  journal={arXiv preprint arXiv:2510.18234},  year={2025}}@article{wei2026deepseek,  title={DeepSeek-OCR 2: Visual Causal Flow},  author={Wei, Haoran and Sun, Yaofeng and Li, Yukun},  journal={arXiv preprint arXiv:2601.20552},  year={2026}}