Image-Text-to-Text
Safetensors
Transformers
English
Chinese
multilingual
dots_mocr
dots_ocr
text-generation
image-to-text
ocr
document-parse
layout
table
formula
custom_code
conversational
Eval Results
Instructions to use dots-studio/dots.mocr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use dots-studio/dots.mocr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="dots-studio/dots.mocr", trust_remote_code=True) messages = [ { "role": "user", "content": [ {"type": "image", "url": "https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/p-blog/candy.JPG"}, {"type": "text", "text": "What animal is on the candy?"} ] }, ] pipe(text=messages)# pip install -U transformers accelerate # Load model directly from transformers import AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("dots-studio/dots.mocr", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use dots-studio/dots.mocr with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "dots-studio/dots.mocr" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dots-studio/dots.mocr", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'Use Docker
docker model run hf.co/dots-studio/dots.mocr
- SGLang
How to use dots-studio/dots.mocr 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 "dots-studio/dots.mocr" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dots-studio/dots.mocr", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }'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 "dots-studio/dots.mocr" \ --host 0.0.0.0 \ --port 30000 # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:30000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "dots-studio/dots.mocr", "messages": [ { "role": "user", "content": [ { "type": "text", "text": "Describe this image in one sentence." }, { "type": "image_url", "image_url": { "url": "https://cdn.britannica.com/61/93061-050-99147DCE/Statue-of-Liberty-Island-New-York-Bay.jpg" } } ] } ] }' - Docker Model Runner
How to use dots-studio/dots.mocr with Docker Model Runner:
docker model run hf.co/dots-studio/dots.mocr
Commit History
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fix: transformers 5.x compat (cache_position + kwargs naming)
Verified signature## Summary This PR fixes two issues that prevent dots.ocr from working with transformers>=5.0: ### 1. cache_position TypeError on generation In transformers 5.x, cache_position is no longer maintained in the generation loop. The current code does `cache_position[0] == 0` which crashes with `TypeError: 'NoneType' object is not subscriptable`. Fix: Use a combined check compatible with both transformers 4.x and 5.x — fall back to `past_key_values is None` when cache_position is unavailable. ### 2. _validate_model_kwargs ValueError for processor outputs forward() uses `**loss_kwargs` instead of `**kwargs`. Transformers 5.x validation only recognizes `**kwargs`/`**model_kwargs` as catch-all params, causing processor outputs like mm_token_type_ids to fail validation. Fix: Rename `**loss_kwargs` to `**kwargs` (functionally identical). ### Backward compatibility Both fixes maintain full backward compatibility with transformers 4.x.3bc1b7d
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Add ParseBench evaluation results (#5)
- Add ParseBench evaluation results (2d42ce5715ff0765648f6611d7e96e159bd0086b) Co-authored-by: boyang zhang <boyang-runllama@users.noreply.huggingface.co>6f8b484 -
Add MDPBench evaluation results (#3)
- Add MDPBench evaluation results (5054d93a4d91136716fba8ce0d1651568c0c0629) Co-authored-by: Delores Lin <Delores-Lin@users.noreply.huggingface.co>92a22a4
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Add OlmOCRBench evaluation results (#1)
- Add OlmOCRBench evaluation results (32238a42a77e4b75a91f0bb22fda49866cef1dc5) Co-authored-by: Niels Rogge <nielsr@users.noreply.huggingface.co>f5a115b
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