Image-Text-to-Text
Transformers
Safetensors
multilingual
internvl_chat
feature-extraction
internvl
custom_code
conversational
Instructions to use OpenGVLab/Mini-InternVL-Chat-2B-V1-5 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use OpenGVLab/Mini-InternVL-Chat-2B-V1-5 with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("image-text-to-text", model="OpenGVLab/Mini-InternVL-Chat-2B-V1-5", 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/Mini-InternVL-Chat-2B-V1-5", trust_remote_code=True, dtype="auto") - Notebooks
- Google Colab
- Kaggle
- Local Apps
- vLLM
How to use OpenGVLab/Mini-InternVL-Chat-2B-V1-5 with vLLM:
Install from pip and serve model
# Install vLLM from pip: pip install vllm # Start the vLLM server: vllm serve "OpenGVLab/Mini-InternVL-Chat-2B-V1-5" # 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/Mini-InternVL-Chat-2B-V1-5", "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/Mini-InternVL-Chat-2B-V1-5
- SGLang
How to use OpenGVLab/Mini-InternVL-Chat-2B-V1-5 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/Mini-InternVL-Chat-2B-V1-5" \ --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/Mini-InternVL-Chat-2B-V1-5", "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/Mini-InternVL-Chat-2B-V1-5" \ --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/Mini-InternVL-Chat-2B-V1-5", "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/Mini-InternVL-Chat-2B-V1-5 with Docker Model Runner:
docker model run hf.co/OpenGVLab/Mini-InternVL-Chat-2B-V1-5
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pipeline_tag: visual-question-answering
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# Model Card for Mini-InternVL-Chat-V1.5
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<p align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/64119264f0f81eb569e0d569/D60YzQBIzvoCvLRp2gZ0A.jpeg" alt="Image Description" width="300" height="300" />
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## Model Usage
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We provide an example code to run Mini-InternVL-Chat-V1.5 using `transformers`.
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You also can use our [online demo](https://internvl.opengvlab.com/) for a quick experience of this model.
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path = "OpenGVLab/Mini-InternVL-Chat-V1-5"
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model = AutoModel.from_pretrained(
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path,
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torch_dtype=torch.bfloat16,
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pipeline_tag: visual-question-answering
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---
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# Model Card for Mini-InternVL-Chat-2B-V1.5
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<p align="center">
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<img src="https://cdn-uploads.huggingface.co/production/uploads/64119264f0f81eb569e0d569/D60YzQBIzvoCvLRp2gZ0A.jpeg" alt="Image Description" width="300" height="300" />
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</p>
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## Model Usage
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We provide an example code to run Mini-InternVL-Chat-2B-V1.5 using `transformers`.
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You also can use our [online demo](https://internvl.opengvlab.com/) for a quick experience of this model.
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return pixel_values
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path = "OpenGVLab/Mini-InternVL-Chat-2B-V1-5"
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model = AutoModel.from_pretrained(
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path,
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torch_dtype=torch.bfloat16,
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