How to Deploy NVIDIA NIM in 5 Minutes
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- čas přidán 10. 09. 2024
- NVIDIA NIM is a set of microservices for deploying AI models. Tap into the latest AI foundation models-like Stable Diffusion, esmfold, and Llama 3-with downloadable NIM microservices for your application deployment.
Join Neal Vaidya, developer advocate at NVIDIA, for a demo on how to quickly deploy NVIDIA NIM microservices, locally with Python or programmatically through Docker. This tutorial focuses on deploying Llama 3.
0:22 - Overview of NIM microservices (nvda.ws/4bZLY9E)
0:36 - Test the Llama 3 model on a web browser with a hosted API
0:51 - Generate an API key and get sample code snippets
0:59 - Test the Llama 3 model in a self-hosted environment
1:08 - Get access to API catalog to begin self-hosted deployment
1:22 - Pre-install Docker engine and Docker CLI tool
1:50 - Authenticate your container
1:55 - Generate an environment variable called NGC API key
2:05 - Input a single Docker run command
2:19 - Expose Docker to all GPUs to the running container
2:28 - Expose the API environment variable
2:35 - Mount the cache to download and store model weights
2:48 - Specify the NIM should run as a local user
2:53 - Expose the main port to interact with the running NIM
3:03 - Add the model name to the image path
3:30 - Confirm the service is ready in another terminal using curl
3:41 - Send the container a new request
Developer resources:
▫️ Learn more about NIM: nvda.ws/3yqsuNw
▫️ Join the NVIDIA Developer Program: nvda.ws/3OhiXfl
▫️ Access downloadable NIM microservices on the API catalog: nvda.ws/4bZLY9E
▫️ Read the Mastering LLM Techniques series to learn about inference optimization, LLM training, and more: resources.nvid...
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Awesome! Thanks, NVIDIA Team!
Things are moving fast! Exciting times !
Very nice tutorial, thanks a lot
Very nice! I will surely have a look at this :)
Nice, thanks 😁
Where is the notebook in the description?
Rip, I think it's this article? Build a RAG using a locally hosted NIM
So... can you make me some money? 😇