Introduction to Llama

Llama has become the most popular open-source LLM, with millions of downloads. This course will teach you how to run Llama models locally, build document Q&A systems, and customize models for your needs, without paying for expensive cloud APIs.
What you'll learn
Privacy regulations and data sensitivity often prevent companies from using cloud-based AI services. In this course, Introduction to Llama, you'll learn to deploy Meta's powerful open-source language models entirely on local hardware.
First, you'll explore the Llama family evolution from research-only models to commercial-friendly releases, understanding critical licensing considerations for different versions.
Next, you'll discover how to run Llama 3.1 8B locally using Ollama on consumer GPUs and integrate it into Python applications.
Finally, you'll learn how to build a retrieval-augmented generation (RAG) system that answers questions in your documents and understands when fine-tuning makes sense vs. using RAG.
When you're finished with this course, you'll have the skills and knowledge of Llama deployments needed to build privacy-preserving AI applications that run entirely on your infrastructure.
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