Image-Text-to-Text
Transformers
Safetensors
English
Chinese
internvl_chat
feature-extraction
visual-language
paddleocr
document-parse
HPD-Parsing
speculative-decoding
P-MTP
eval results
conversational
custom_code
Instructions to use PaddlePaddle/HPD-Parsing with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use PaddlePaddle/HPD-Parsing with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="PaddlePaddle/HPD-Parsing", 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)# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("PaddlePaddle/HPD-Parsing", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use PaddlePaddle/HPD-Parsing with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "PaddlePaddle/HPD-Parsing" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "PaddlePaddle/HPD-Parsing", "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/PaddlePaddle/HPD-Parsing
- SGLang
How to use PaddlePaddle/HPD-Parsing 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 "PaddlePaddle/HPD-Parsing" \ --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": "PaddlePaddle/HPD-Parsing", "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 "PaddlePaddle/HPD-Parsing" \ --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": "PaddlePaddle/HPD-Parsing", "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 PaddlePaddle/HPD-Parsing with Docker Model Runner:
docker model run hf.co/PaddlePaddle/HPD-Parsing
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If you find HPD-Parsing helpful, feel free to give us a star and citation.
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```bibtex
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@misc{
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title={HPD-Parsing: Hierarchical Parallel Document Parsing},
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author={Shu Wei and Jingjing Wu and Lingshu Zhang and Qunyi Xie and Hao Zou and Le Xiang and Xu Fan and Yangliu Xu and Manhui Lin and Xiaolong Ma and Cheng Cui and Tengyu Du and YY},
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year={2026},
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}
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```
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If you find HPD-Parsing helpful, feel free to give us a star and citation.
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```bibtex
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@misc{wei2026hpdparsinghierarchicalparalleldocument,
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title={HPD-Parsing: Hierarchical Parallel Document Parsing},
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author={Shu Wei and Jingjing Wu and Lingshu Zhang and Qunyi Xie and Hao Zou and Le Xiang and Xu Fan and Yangliu Xu and Manhui Lin and Xiaolong Ma and Cheng Cui and Tengyu Du and YY},
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year={2026},
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eprint={2607.18839},
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archivePrefix={arXiv},
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primaryClass={cs.CL},
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url={https://arxiv.org/abs/2607.18839},
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}
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```
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