Image-Text-to-Text
Transformers
Safetensors
multilingual
hunyuan_vl
text-generation
ocr
hunyuan
vision-language
image-to-text
1B
end-to-end
conversational
Eval Results
Instructions to use tencent/HunyuanOCR with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use tencent/HunyuanOCR with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="tencent/HunyuanOCR") 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 AutoModelForSeq2SeqLM model = AutoModelForSeq2SeqLM.from_pretrained("tencent/HunyuanOCR", dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use tencent/HunyuanOCR with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "tencent/HunyuanOCR" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "tencent/HunyuanOCR", "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/tencent/HunyuanOCR
- SGLang
How to use tencent/HunyuanOCR 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 "tencent/HunyuanOCR" \ --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": "tencent/HunyuanOCR", "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 "tencent/HunyuanOCR" \ --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": "tencent/HunyuanOCR", "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 tencent/HunyuanOCR with Docker Model Runner:
docker model run hf.co/tencent/HunyuanOCR
Update config.json
Browse files- config.json +3 -3
config.json
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"anyres_vit_max_image_size": 2048,
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"anyres_vit_two_views": false,
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"architectures": [
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"
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"attention_bias": false,
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"attention_dropout": 0.0,
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"max_position_embeddings": 32768,
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"tie_word_embeddings": true,
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"mlp_bias": false,
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"model_type": "
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"moe_drop_tokens": false,
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"moe_intermediate_size": null,
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"moe_layer_num_skipped": 0,
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"factor": 1.0,
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"mscale": 1.0,
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"mscale_all_dim": 1.0,
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"type": "
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"rope_theta": 10000.0,
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"routed_scaling_factor": 1.0,
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"anyres_vit_max_image_size": 2048,
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"anyres_vit_two_views": false,
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"architectures": [
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"HunYuanVLForConditionalGeneration"
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],
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"attention_bias": false,
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"attention_dropout": 0.0,
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"max_position_embeddings": 32768,
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"tie_word_embeddings": true,
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"mlp_bias": false,
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"model_type": "hunyuan_vl",
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"moe_drop_tokens": false,
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"moe_intermediate_size": null,
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"moe_layer_num_skipped": 0,
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"factor": 1.0,
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"mscale": 1.0,
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"mscale_all_dim": 1.0,
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"type": "xdrope"
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},
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"rope_theta": 10000.0,
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"routed_scaling_factor": 1.0,
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