Image-Text-to-Text
Transformers
Safetensors
multilingual
internvl_chat
feature-extraction
internvl
vision
ocr
custom_code
Mixture of Experts
conversational
Instructions to use OpenGVLab/Mono-InternVL-2B-S1-2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/Mono-InternVL-2B-S1-2 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="OpenGVLab/Mono-InternVL-2B-S1-2", 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 AutoModel model = AutoModel.from_pretrained("OpenGVLab/Mono-InternVL-2B-S1-2", trust_remote_code=True, device_map="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- vLLM
How to use OpenGVLab/Mono-InternVL-2B-S1-2 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenGVLab/Mono-InternVL-2B-S1-2" # 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/Mono-InternVL-2B-S1-2", "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/Mono-InternVL-2B-S1-2
- SGLang
How to use OpenGVLab/Mono-InternVL-2B-S1-2 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/Mono-InternVL-2B-S1-2" \ --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/Mono-InternVL-2B-S1-2", "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/Mono-InternVL-2B-S1-2" \ --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/Mono-InternVL-2B-S1-2", "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/Mono-InternVL-2B-S1-2 with Docker Model Runner:
docker model run hf.co/OpenGVLab/Mono-InternVL-2B-S1-2
Commit History
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Update model card with Mono-InternVL-1.5 paper details and expanded information
Verified signatureThis PR significantly enhances the model card for Mono-InternVL-2B-S1-2. It updates the primary paper reference to [Mono-InternVL-1.5: Towards Cheaper and Faster Monolithic Multimodal Large Language Models](https://huggingface.co/papers/2507.12566), which details recent advancements relevant to this model. Additionally, it incorporates comprehensive details from the project's GitHub README, including: - **News updates** - A detailed **Introduction** to the Mono-InternVL architecture and principles - **Performance benchmarks** - **Inference code examples** using `transformers` and `lmdeploy` - **Supervised Finetuning** instructions - An updated **Citation** section to include both Mono-InternVL V1 and V1.5 papers - A clear **License** section. The "File information" section has been removed as it's not standard model card content. This update provides users with a much richer and more informative resource for understanding and utilizing the model.a76dfd5
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Update README.md (#1)
Verified signature- Update README.md (accf640c2559544f4c75ffc67d8526f4d74c01e8) Co-authored-by: Zhaokai Wang <wzk1015@users.noreply.huggingface.co>ec0cc57
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Add model files
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initial commit
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