Self-Host and Deploy Local LLAMA-3 with NIMs

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​ In this video, I walk you through deploying Llama models using NVIDIA NIM. NVIDIA NIM uses microservices to enhance the deployment of various AI models, offering up to three times improvement in performance. I demonstrate how to set up an NVIDIA Launchpad, deploy the Llama 3 8 billion instruct version, and stress test it to see throughput. I also show you how to utilize OpenAI compatible API servers with NVIDIA NIM.

LINKS:
NIM: https://nvda.ws/44u5KYH
https://org.ngc.nvidia.com/setup/personal-keys
NIM Previous Video: https://youtu.be/l8_fVTWmkNA

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TIMESTAMPS
00:00 Introduction to Deploying Large Language Models
00:13 Overview of NVIDIA NIM
01:02 Setting Up and Deploying a NIM
01:51 Accessing and Monitoring the GPU
03:39 Generating API Keys and Running Docker
05:36 Interacting with the Deployed Model
07:16 Stress Testing the API Endpoint
09:53 Using OpenAI Compatible API with NVIDIA NIM
12:32 Conclusion and Next Steps

All Interesting Videos:
Everything LangChain: https://www.youtube.com/playlist?list=PLVEEucA9MYhOu89CX8H3MBZqayTbcCTMr

Everything LLM: https://youtube.com/playlist?list=PLVEEucA9MYhNF5-zeb4Iw2Nl1OKTH-Txw

Everything Midjourney: https://youtube.com/playlist?list=PLVEEucA9MYhMdrdHZtFeEebl20LPkaSmw

AI Image Generation: https://youtube.com/playlist?list=PLVEEucA9MYhPVgYazU5hx6emMXtargd4z   Read More Prompt Engineering 

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