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    NVIDIA

    llama-3.1-nemoguard-8b-content-safety

    Downloadable

    Leading content safety model for enhancing the safety and moderation capabilities of LLMs

    • LLM safety
    • Safety and moderation
    • dialogue safety
    • nemo guardrails
    • nemotron
    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 following command. This command downloads the optimized model for your infrastructure.

    export NGC_API_KEY=<PASTE_API_KEY_HERE>
export LOCAL_NIM_CACHE=~/.cache/contentsafety
mkdir -p "$LOCAL_NIM_CACHE"
docker run -it --rm \
    --runtime=nvidia \
    --gpus=all \
    --shm-size=16GB \
    -e NGC_API_KEY \
    -e NIM_SERVED_MODEL_NAME="llama-3.1-nemoguard-8b-content-safety" \
    -e NIM_CUSTOM_MODEL_NAME="llama-3.1-nemoguard-8b-content-safety" \
    -v "$LOCAL_NIM_CACHE:/opt/nim/.cache" \
    -u $(id -u) \
    -p 8000:8000 \
    nvcr.io/nim/nvidia/llama-3.1-nemoguard-8b-content-safety:latest

    Step 3
    Test the NIM

    Checking content safety requires careful set up of a prompt and parsing the model response. Refer to Running Inference in the product documentation.

    For more information about getting started with this NIM, refer to Llama 3.1 NemoGuard 8B ContentSafety NIM.