L-10 RAG Vs Fine-tuning

Generative AI Tutorials

In this video, we'll dive into the differences between Retrieval-Augmented Generation (RAG) and fine-tuned models. We'll explore how each approach enhances language models and when to use them. A fine-tuned model begins with a pre-trained language model, such as LLaMA, Mistral, Gemini, GPT-3.5, or GPT-4. We then train this model further on a specific dataset. The model generates responses based on the knowledge it acquired during this training phase. Retrieval-Augmented Generation (RAG) allows us to provide external, up-to-date knowledge to the model.

About the course

Welcome to our Generative AI playlist! This curated collection of videos explores the exciting and rapidly evolving field of Generative Artificial Intelligence. Throughout this playlist, you'll find comprehensive guides on various large language models (LLMs), including their capabilities, applications, and how to utilize them effectively. We'll also dive deep into LangChain, a powerful tool for building generative AI applications. Whether you're a beginner looking to understand the basics or an experienced developer seeking advanced insights, this playlist has something for everyone. Join us as we uncover the potential of Generative AI and learn how to leverage it for innovative solutions!