Image-Text-to-Text
Transformers
Safetensors
multilingual
unlimited-ocr
feature-extraction
baidu
vision-language
ocr
custom_code
Eval Results
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, device_map="auto")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("baidu/Unlimited-OCR", trust_remote_code=True, dtype="auto", device_map="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
#4
by boyang-runllama - opened
.eval_results/parsebench.yaml
ADDED
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- dataset:
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id: llamaindex/ParseBench
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task_id: mean
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value: 46.17
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date: '2026-06-24'
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source:
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url: https://huggingface.co/datasets/llamaindex/ParseBench
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name: ParseBench
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user: boyang-runllama
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notes: "Pipeline name: unlimitedocr"
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- dataset:
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id: llamaindex/ParseBench
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task_id: text_content
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value: 86.81
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date: '2026-06-24'
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source:
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url: https://huggingface.co/datasets/llamaindex/ParseBench
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name: ParseBench
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user: boyang-runllama
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notes: "Pipeline name: unlimitedocr"
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- dataset:
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id: llamaindex/ParseBench
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task_id: text_formatting
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value: 0.97
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date: '2026-06-24'
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source:
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url: https://huggingface.co/datasets/llamaindex/ParseBench
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name: ParseBench
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user: boyang-runllama
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notes: "Pipeline name: unlimitedocr"
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- dataset:
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id: llamaindex/ParseBench
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task_id: layout
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value: 71.52
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date: '2026-06-24'
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source:
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url: https://huggingface.co/datasets/llamaindex/ParseBench
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name: ParseBench
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user: boyang-runllama
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notes: "Pipeline name: unlimitedocr"
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- dataset:
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id: llamaindex/ParseBench
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task_id: chart
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value: 1.34
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date: '2026-06-24'
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source:
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url: https://huggingface.co/datasets/llamaindex/ParseBench
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name: ParseBench
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user: boyang-runllama
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notes: "Pipeline name: unlimitedocr"
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- dataset:
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id: llamaindex/ParseBench
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task_id: table
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value: 70.21
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date: '2026-06-24'
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source:
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url: https://huggingface.co/datasets/llamaindex/ParseBench
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name: ParseBench
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user: boyang-runllama
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notes: "Pipeline name: unlimitedocr"
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