Image-Text-to-Text
Transformers
Safetensors
multilingual
internvl_chat
image-feature-extraction
internvl
vision-language model
monolithic
conversational
custom_code
Instructions to use OpenGVLab/HoVLE with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/HoVLE with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="OpenGVLab/HoVLE", 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("OpenGVLab/HoVLE", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OpenGVLab/HoVLE with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenGVLab/HoVLE" # Call the server using curl (OpenAI-compatible API): curl -X POST "http://localhost:8000/v1/chat/completions" \ -H "Content-Type: application/json" \ --data '{ "model": "OpenGVLab/HoVLE", "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/OpenGVLab/HoVLE
- SGLang
How to use OpenGVLab/HoVLE 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 "OpenGVLab/HoVLE" \ --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": "OpenGVLab/HoVLE", "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 "OpenGVLab/HoVLE" \ --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": "OpenGVLab/HoVLE", "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 OpenGVLab/HoVLE with Docker Model Runner:
docker model run hf.co/OpenGVLab/HoVLE
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# HoVLE
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[\[📜 HoVLE Paper\]]() [\[🚀 Quick Start\]](#quick-start)
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HoVLE significantly surpasses previous monolithic VLMs and demonstrates competitive performance with compositional VLMs. This work narrows the gap between monolithic and compositional VLMs, providing a promising direction for the development of monolithic VLMs.
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This repository releases the HoVLE model with 2.6B parameters. It is built upon [internlm2-chat-1_8b](https://huggingface.co/internlm/internlm2-chat-1_8b). Please refer to [HoVLE (HD)](https://huggingface.co/OpenGVLab/HoVLE-HD) for the high-definition version. For more details, please refer to our [paper]().
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## Model Details
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# HoVLE
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[\[📜 HoVLE Paper\]](https://arxiv.org/pdf/2412.16158) [\[🚀 Quick Start\]](#quick-start)
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HoVLE significantly surpasses previous monolithic VLMs and demonstrates competitive performance with compositional VLMs. This work narrows the gap between monolithic and compositional VLMs, providing a promising direction for the development of monolithic VLMs.
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This repository releases the HoVLE model with 2.6B parameters. It is built upon [internlm2-chat-1_8b](https://huggingface.co/internlm/internlm2-chat-1_8b). Please refer to [HoVLE (HD)](https://huggingface.co/OpenGVLab/HoVLE-HD) for the high-definition version. For more details, please refer to our [paper](https://arxiv.org/pdf/2412.16158).
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## Model Details
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