nvidia/nv-embedqa-e5-v5

RUN ANYWHERE

English text embedding model for question-answering retrieval.

Embedding
nemo retriever
Retrieval Augmented Generation
Text-to-Embedding
API Reference

By running the below commands, you accept the NVIDIA AI Enterprise Terms of Use and the NVIDIA Community Models License.

Pull and run nvidia/nv-embedqa-e5-v5 using Docker (this will download the full model and run it in your local environment)

$ 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/nv-embedqa-e5-v5: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 '{
    "input": ["Hello world"],
    "model": "nvidia/nv-embedqa-e5-v5",
    "input_type": "query"
}'

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