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llama-3.2-11b-vision-instruct

Run Anywhere

Cutting-edge vision-language model exceling in high-quality reasoning from images.

image captioningimage-text retrievalvisual groundingvisual qaimage-to-text
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API Reference
Accelerated by DGX Cloud
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Follow the steps below to download and run the NVIDIA NIM inference microservice for this model on your infrastructure of choice.

Step 1
Generate API Key

Step 2
Pull and Run the NIM

$ docker login nvcr.io Username: $oauthtoken Password: <PASTE_API_KEY_HERE>

Pull and run the NVIDIA NIM with the command below. This will download the optimized model for your infrastructure.

export NGC_API_KEY=<PASTE_API_KEY_HERE> export LOCAL_NIM_CACHE=~/.cache/nim mkdir -p "$LOCAL_NIM_CACHE" docker run -it --rm \ --gpus all \ --shm-size=16GB \ -e NGC_API_KEY \ -v "$LOCAL_NIM_CACHE:/opt/nim/.cache" \ -u $(id -u) \ -p 8000:8000 \ nvcr.io/nim/meta/llama-3.2-11b-vision-instruct:latest

Step 3
Test the NIM

You can now make a local API call using this curl command:

curl -X 'POST' \ 'http://0.0.0.0:8000/v1/chat/completions' \ -H 'accept: application/json' \ -H 'Content-Type: application/json' \ -d '{ "model": "meta/llama-3.2-11b-vision-instruct", "messages": [{"role":"user", "content":[ {"type": "text", "text": "Describe this image"}, { "type": "image_url", "image_url": {"url": "https://assets.ngc.nvidia.com/products/api-catalog/phi-3-5-vision/example1b.jpg"} } ]}], "max_tokens": 256 }'

For more details on getting started with this NIM, visit the NVIDIA NIM Docs.