Distilled version of Llama 3.1 8B using reasoning data generated by DeepSeek R1 for enhanced performance.
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/deepseek-ai/deepseek-r1-distill-llama-8b:1.5.2
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": "deepseek-ai/deepseek-r1-distill-llama-8b", "messages": [{"role":"user", "content":"Which number is larger, 9.11 or 9.8?"}], "max_tokens": 64 }'
For more details on getting started with this NIM, visit the NVIDIA NIM Docs.