
1B embedding model for semantic search, retrieval, and RAG applications.
Follow the steps below to download and run the NVIDIA NIM inference microservice for this model on your infrastructure of choice.
$ 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/nemotron-3-embed-1b:latest
You can now make a local API call using this curl command:
curl -X "POST" \
"http://localhost:8000/v1/embeddings" \
-H 'accept: application/json' \
-H 'Content-Type: application/json' \
-d '{
"model": "nvidia/nemotron-3-embed-1b",
"input": "What symptoms and common triggers help distinguish eczema from other inflammatory skin conditions?",
"input_type": "query",
"encoding_format": "float",
"truncate": "END"
}'
For more details on getting started with this NIM, visit the NVIDIA NIM Docs.