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unsloth/DeepSeek-OCR-2

sourceHugging Faceapache-2.0updated 3mo agoView on Hugging Face

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Read our Guide How to: Run & Fine-tune DeepSeek-OCR 2.

<div> <p style="margin-top: 0;margin-bottom: 0;"> <em>This DeepSeek-OCR 2 upload was edited to enable inference & fine-tuning on the latest transformers (no accuracy change).</em> </p> <div style="display: flex; gap: 5px; align-items: center; "> <a href="https://github.com/unslothai/unsloth/"> <img src="https://github.com/unslothai/unsloth/raw/main/images/unsloth%20new%20logo.png" width="133"> </a> <a href="https://discord.gg/unsloth"> <img src="https://github.com/unslothai/unsloth/raw/main/images/Discord%20button.png" width="173"> </a> <a href="https://docs.unsloth.ai/models/deepseek-ocr-2"> <img src="https://raw.githubusercontent.com/unslothai/unsloth/refs/heads/main/images/documentation%20green%20button.png" width="143"> </a> </div> <h1 style="margin-top: 0rem;">✨ Read our DeepSeek-OCR 2 Guide <a href="https://docs.unsloth.ai/models/deepseek-ocr-2">here</a>!</h1> </div>

—Fine-tune DeepSeek-OCR 2 for free using our Google Colab notebook.ipynb)
—View the rest of our notebooks in our docs here.

</div>

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<p align="center"> <a href="https://github.com/deepseek-ai/DeepSeek-OCR-2"><b>🌟 Github</b></a> | <a href="https://huggingface.co/deepseek-ai/DeepSeek-OCR-2"><b>📥 Model Download</b></a> | <a href="https://github.com/deepseek-ai/DeepSeek-OCR-2/blob/main/DeepSeekOCR2paper.pdf"><b>📄 Paper Link</b></a> | <a href="https://github.com/deepseek-ai/DeepSeek-OCR-2/blob/main/DeepSeekOCR2paper.pdf"><b>📄 Arxiv Paper Link</b></a> | </p> <h2> <p align="center"> <a href="">DeepSeek-OCR 2: Visual Causal Flow</a> </p> </h2> <p align="center"> <img src="assets/fig1.png" style="width: 900px" align=center> </p> <p align="center"> <a href="">Explore more human-like visual encoding.</a> </p>

Usage

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

torch==2.6.0
transformers==4.46.3
tokenizers==0.20.3
einops
addict 
easydict
pip install flash-attn==2.7.3 --no-build-isolation

python

from transformers import AutoModel, AutoTokenizer
import torch
import os
os.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 ✅

Prompts examples

python

# document: <image>\n<|grounding|>Convert the document to markdown.
# other image: <image>\n<|grounding|>OCR this image.
# without layouts: <image>\nFree OCR.
# figures in document: <image>\nParse the figure.
# general: <image>\nDescribe this image in detail.
# rec: <image>\nLocate <|ref|>xxxx<|/ref|> in the image.

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

coming soon~