How to Improve LLMs with RAG (Overview + Python Code) скачать в хорошем качестве

How to Improve LLMs with RAG (Overview + Python Code)

💡 Get 30 (free) AI project ideas: https://30aiprojects.com/ In this video, I give a beginner-friendly introduction to retrieval augmented generation (RAG) and show how to use it to improve a fine-tuned model from a previous video in this LLM series. ▶️ Series Playlist:    • Large Language Models (LLMs)   🎥 Fine-tuning with QLoRA:    • QLoRA—How to Fine-tune an LLM on a Single ...   📰 Read more: https://medium.com/towards-data-scien... 💻 Colab: https://colab.research.google.com/dri... 💻 GitHub: https://github.com/ShawhinT/YouTube-B... 🤗 Model: https://huggingface.co/shawhin/shawgp... References [1] https://github.com/openai/openai-cook... [2]    • LlamaIndex Webinar: Building LLM Apps for ...   [3] https://docs.llamaindex.ai/en/stable/... [4]    • LlamaIndex Webinar: Make RAG Production-Ready   -- Homepage: https://www.shawhintalebi.com/ Book a call: https://calendly.com/shawhintalebi Intro - 0:00 Background - 0:53 2 Limitations - 1:45 What is RAG? - 2:51 How RAG works - 5:03 Text Embeddings + Retrieval - 5:35 Creating Knowledge Base - 7:37 Example Code: Improving YouTube Comment Responder with RAG - 9:34 What's next? - 20:58