GitHub AI Repos
Discover popular open-source AI projects. Explore libraries, runtimes, agents, databases, and frameworks categorized by programming languages and GitHub stars.
21 Lessons, Get Started Building with Generative AI
Implement a ChatGPT-like LLM in PyTorch from scratch, step by step
Ready-to-run cloud templates for RAG, AI pipelines, and enterprise search with live data. 🐳Docker-friendly.⚡Always in sync with Sharepoint, Google Drive, S3, Kafka, PostgreSQL, real-time data APIs, and more.
In-depth tutorials on LLMs, RAGs and real-world AI agent applications.
《开源大模型食用指南》针对中国宝宝量身打造的基于Linux环境快速微调(全参数/Lora)、部署国内外开源大模型(LLM)/多模态大模型(MLLM)教程
This repository showcases various advanced techniques for Retrieval-Augmented Generation (RAG) systems. Each technique has a detailed notebook tutorial.
Official code repo for the O'Reilly Book - "Hands-On Large Language Models"
This repository is maintained by Omar Santos (@santosomar) and includes thousands of resources related to ethical hacking, bug bounties, digital forensics and incident response (DFIR), AI security, vulnerability research, exploit development, reverse engineering, and more. 🔥 Also check: https://hackertraining.org
50+ tutorials and implementations for Generative AI Agent techniques, from basic conversational bots to complex multi-agent systems.
✅(已完结)超级全面的 深度学习 笔记【土堆 Pytorch】【李沐 动手学深度学习】【吴恩达 深度学习】【大飞 大模型Agent】
End-to-end, code-first tutorials for building production-grade GenAI agents. From prototype to enterprise deployment.
Welcome to the Llama Cookbook! This is your go to guide for Building with Llama: Getting started with Inference, Fine-Tuning, RAG. We also show you how to solve end to end problems using Llama model family and using them on various provider services
Sample code and notebooks for Generative AI on Google Cloud, with Gemini Enterprise Agent Platform
This open-source curriculum introduces the fundamentals of Model Context Protocol (MCP) through real-world, cross-language examples in .NET, Java, TypeScript, JavaScript, Rust and Python. Designed for developers, it focuses on practical techniques for building modular, scalable, and secure AI workflows from session setup to service orchestration.
本项目是一个面向小白开发者的大模型应用开发教程,在线阅读地址:https://datawhalechina.github.io/llm-universe/