The video demonstrates deploying Llama models using NVIDIA NIM, which utilizes microservices to enhance AI model deployment and offers up to three times improvement in performance. The process includes setting up an NVIDIA Launchpad, deploying the Llama 3 8 billion instruct version, stress testing it for throughput, and utilizing OpenAI compatible API servers with NVIDIA NIM. The video provides links to NIM, personal keys setup, and previous videos for reference. Additional resources such as the RAG Beyond Basics Course, Discord, Patreon, and consulting services are also shared. The video includes timestamps for different sections, such as an introduction to deploying large language models, setting up and deploying NIM, accessing and monitoring the GPU, generating API keys, interacting with the deployed model, stress testing the API endpoint, and using OpenAI compatible API with NVIDIA NIM. The video concludes with next steps and links to other related videos on LangChain, LLM, Midjourney, and AI image generation. Viewers can also access a pre-configured localGPT VM and sign up for the newsletter.
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Source link: https://www.youtube.com/watch?v=OuQBxBrO2ms
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Deploy LLAMA-3 with NIMs on Local Server #SelfHostDeployment
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