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 for Long Chain-of-Thought (Long-CoT) reasoning in LLMs, featuring papers, implementations, and datasets to track the latest advancements in the field.
A curated collection of recent research papers on autonomous agents, focusing on both reinforcement learning-based and large language model-based approaches, helping researchers quickly understand the cutting edge of the field。
A curated list of research on Embodied AI or robots with Large Language Models that tracks the latest developments in this field.
A comprehensive, curated collection of resources for Azure OpenAI, Large Language Models (LLMs), and their applications, featuring tools, frameworks, best practices, and research papers.
An awesome list that summarizes open-source repositories for training LLM agents using reinforcement learning, categorized into base frameworks, general/multi-task, search/research/web, GUI, and tool-based agents.
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 curated repository collecting papers on Large Language Model (LLM) based agents, primarily based on the 86-page systematic survey paper "The Rise and Potential of Large Language Model Based Agents: A Survey" by Zhiheng Xi et al.
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.
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