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Happy LLM

LLM Frameworks

A free, open‑source tutorial series that teaches you how to understand and build large language models (LLMs) from the basics of NLP up through training an LLaMA2 model.

Track releases GitHub Website
Jupyter Notebook Latest v1.0.2 · 5mo ago Security brief →

Features

  • Systematic learning path covering NLP fundamentals, Transformer architecture, and LLM principles
  • Hands‑on implementation guides for building and training a complete LLaMA2 model
  • End‑to‑end coverage of pre‑training, supervised fine‑tuning, and efficient PEFT techniques (LoRA/QLoRA)
  • Practical applications such as Retrieval‑Augmented Generation (RAG) and Agent frameworks

Recent releases

View all 1 releases →
v1.0.2 New feature
Notable features
  • Accompanying teaching lecture PPT resources added
Full changelog

Happy-LLM v1.0.2 0129 PPT 发布！

  • 新增配套教学讲义PPT课件资源。

  本 Happy-LLM PDF 教程完全开源免费。为防止各类营销号加水印后贩卖给大模型初学者，我们特地在 PDF 文件中预先添加了不影响阅读的 Datawhale 开源标志水印，敬请谅解～

  This Happy-LLM PDF tutorial is completely open-source and free. To prevent third-party marketing accounts from adding watermarks and selling it to LLM beginners, we have pre-added a non-intrusive Datawhale open-source logo watermark to the PDF file. Kindly understand~

在线阅读地址：https://datawhalechina.github.io/happy-llm/
Happy-LLM：https://github.com/datawhalechina/happy-llm
PPT 获取地址：https://github.com/HZAI-ZJNU/happy-llm-ppt
Datawhale ：https://www.datawhale.cn/home

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