Image-Text-to-Text
Safetensors
Transformers
English
Chinese
multilingual
dots_ocr
text-generation
image-to-text
ocr
document-parse
layout
table
formula
custom_code
conversational
Eval Results
Instructions to use rednote-hilab/dots.ocr with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use rednote-hilab/dots.ocr with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="rednote-hilab/dots.ocr", 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 AutoModelForCausalLM model = AutoModelForCausalLM.from_pretrained("rednote-hilab/dots.ocr", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use rednote-hilab/dots.ocr with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "rednote-hilab/dots.ocr" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "rednote-hilab/dots.ocr", "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/rednote-hilab/dots.ocr
- SGLang
How to use rednote-hilab/dots.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 "rednote-hilab/dots.ocr" \ --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": "rednote-hilab/dots.ocr", "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 "rednote-hilab/dots.ocr" \ --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": "rednote-hilab/dots.ocr", "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 rednote-hilab/dots.ocr with Docker Model Runner:
docker model run hf.co/rednote-hilab/dots.ocr
Update modeling_dots_ocr_vllm.py
Browse files- modeling_dots_ocr_vllm.py +11 -0
modeling_dots_ocr_vllm.py
CHANGED
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@@ -91,6 +91,17 @@ class DotsOCRProcessingInfo(Qwen2_5_VLProcessingInfo):
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return config
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def get_hf_processor(
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self,
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*,
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return config
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def get_supported_mm_limits(self) -> Mapping[str, Optional[int]]:
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return {"image": None, "video": 0}
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def get_mm_max_tokens_per_item(
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self,
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seq_len: int,
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mm_counts: Mapping[str, int],
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) -> Mapping[str, int]:
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max_image_tokens = self.get_max_image_tokens()
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return {"image": max_image_tokens, "video": 0}
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def get_hf_processor(
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self,
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*,
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