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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.
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💻 RAG Beyond Basics Course:
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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:
LINKS:
💻 RAG Beyond Basics Course:
Let's Connect:
Signup for Newsletter, localgpt:
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:
Self-Host and Deploy Local LLAMA-3 with NIMs
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