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    NVIDIA

    nemoretriever-parse

    DeprecatedDownloadable

    Cutting-edge vision-language model exceling in retrieving text and metadata from images.

    • data ingestion
    • nemo retriever
    • optical character recognition
    • supported language - english
    • table extraction
    Get API Key
    API ReferenceAPI Reference
    Accelerated by DGX Cloud
    Deploying your application in production? Get started with a 90-day evaluation of NVIDIA AI Enterprise

    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/nvidia/nemoretriever-parse: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": "nvidia/nemoretriever-parse",
        "messages": [{"role":"user", "content":[
            {
              "type": "image_url",
              "image_url": {"url": "https://assets.ngc.nvidia.com/products/api-catalog/nemoretriever-parse/example_1.jpg"}
            }
        ]}],
        "max_tokens": 256
    }'
    

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