Instructions to use baidu/Unlimited-OCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use baidu/Unlimited-OCR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="baidu/Unlimited-OCR", trust_remote_code=True)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("baidu/Unlimited-OCR", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use baidu/Unlimited-OCR with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "baidu/Unlimited-OCR" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "baidu/Unlimited-OCR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }'Use Docker
docker model run hf.co/baidu/Unlimited-OCR
- SGLang
How to use baidu/Unlimited-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 "baidu/Unlimited-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": "baidu/Unlimited-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 "baidu/Unlimited-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": "baidu/Unlimited-OCR", "prompt": "Once upon a time,", "max_tokens": 512, "temperature": 0.5 }' - Docker Model Runner
How to use baidu/Unlimited-OCR with Docker Model Runner:
docker model run hf.co/baidu/Unlimited-OCR
Add ParseBench evaluation results
This PR ensures your model shows up at https://huggingface.co/datasets/llamaindex/ParseBench.
This is based on the new evaluation results feature: https://huggingface.co/docs/hub/eval-results.
Note: this includes per-dimension performance across all 5 ParseBench dimensions (text_content, text_formatting, layout, chart, table) along with the overall mean score.
Worth a caveat next to these numbers. On clean, structured pages it scores well, which is most of what ParseBench measures. On faint or low quality scans it hallucinates when it can't read the text it invents plausible content instead of leaving it blank.
In a side by side which I performed, it was the LEAST faithful of several OCR models -
olmOCR-2 > Qianfan-OCR > PaddleOCR-VL > HunyuanOCR > Unlimited-OCR
can you share your training data