Instructions to use deepseek-ai/DeepSeek-OCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use deepseek-ai/DeepSeek-OCR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="deepseek-ai/DeepSeek-OCR", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("deepseek-ai/DeepSeek-OCR", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use deepseek-ai/DeepSeek-OCR with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "deepseek-ai/DeepSeek-OCR" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "deepseek-ai/DeepSeek-OCR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/deepseek-ai/DeepSeek-OCR
- SGLang
How to use deepseek-ai/DeepSeek-OCR with SGLang:
Install from pip and serve model
# Install SGLang from pip: pip install sglang # Start the SGLang server: python3 -m sglang.launch_server \ --model-path "deepseek-ai/DeepSeek-OCR" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "deepseek-ai/DeepSeek-OCR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker images
docker run --gpus all \ --shm-size 32g \ -p 30000:30000 \ -v ~/.cache/huggingface:/root/.cache/huggingface \ --env "HF_TOKEN=<secret>" \ --ipc=host \ lmsysorg/sglang:latest \ python3 -m sglang.launch_server \ --model-path "deepseek-ai/DeepSeek-OCR" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "deepseek-ai/DeepSeek-OCR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use deepseek-ai/DeepSeek-OCR with Docker Model Runner:
docker model run hf.co/deepseek-ai/DeepSeek-OCR
RuntimeError: The expanded size of the tensor (753) must match the existing size (752) at non-singleton dimension 0. Target sizes: [753, 1280]. Tensor sizes: [752, 1]
I encountered the above error when running your reference inference code, but with eager attention implementation (I can't get FA2 to run properly - same issue as listed here: https://huggingface.co/deepseek-ai/DeepSeek-OCR/discussions/7 )
Traceback:
File "deepseekocr/modeling_deepseekocr.py", line 506, in forward
inputs_embeds[idx].masked_scatter_(images_seq_mask[idx].unsqueeze(-1), images_in_this_batch)
System specs:
WSL (Ubuntu)
Python 3.12
Torch 2.6 + cu124
Transformers 4.57.1
Some help would be appreciated.
Hi. You are using the latest transformers (4.57.1), but Deepseek-OCR uses 4.46.3 . The latest version uses -1 to indicate an infinite kvcache space, instead of None type. So this slight type difference makes attention_mask is 1 shorter than inputs_embeds, i.e. 752 vs 753 in your log.
To solve it, you can downgrade your transformers version. Or checkout my PR/96.