Retraining vs RAG vs Context - Using Local Data on Large Language Models
Offered By: Dave's Garage via YouTube
Course Description
Overview
Explore the methods of expanding large language model functionality through retraining, retrieval augmented generation (RAG), and context documents in this informative video. Learn how these techniques can be applied to both local and online models to enhance their capabilities. Gain insights into the differences between these approaches and understand their practical applications in leveraging local data with LLMs. Discover how these methods can be used to customize and improve AI models for specific tasks or domains.
Syllabus
Retraining vs RAG vs Context: Your Local Data on LLMs!
Taught by
Dave's Garage
Related Courses
Pinecone Vercel Starter Template and RAG - Live Code Review Part 2Pinecone via YouTube Will LLMs Kill Search? The Future of Information Retrieval
Aleksa Gordić - The AI Epiphany via YouTube RAG But Better: Rerankers with Cohere AI - Improving Retrieval Pipelines
James Briggs via YouTube Advanced RAG - Contextual Compressors and Filters - Lecture 4
Sam Witteveen via YouTube LangChain Multi-Query Retriever for RAG - Advanced Technique for Broader Vector Space Search
James Briggs via YouTube