Official code repository for the O'Reilly book "Hands-On Large Language Models". Features 12 core chapters and bonus content covering Tokens, Transformers, RAG, and Fine-tuning. Includes 300+ illustrations and runnable Jupyter Notebooks optimized for Colab and local environments.
A comprehensive AI engineering hub featuring 93+ production-ready projects with in-depth tutorials and implementations for LLMs, RAGs, AI Agents, and MCP, covering beginner to advanced skill levels.
A curated collection of resources that bridge the gap between Retrieval-Augmented Generation (RAG) and Reasoning in Large Language Models and Agents, featuring papers, tools, and implementations.
A collection of Jupyter notebooks accompanying the "Building LLMs for Production" book by Towards AI, providing practical tutorials on RAG, LLMs, prompt engineering, fine-tuning, and more.
A curated collection of papers and blogs on Large Language Model based Long Context Modeling, covering Efficient Transformers, Length Extrapolation, Long Term Memory, Retrieval Augmented Generation (RAG), and Evaluation methods。
Page 1 / 1 · 5 total
Get the latest AI tools and trends delivered straight to your inbox. No spam, just intelligence.
