Show HN: How-to-train-your-GPT. Every line commented (github.com)

A new interactive guide titled "How-to-train-your-GPT" has been launched, designed to teach users how to build and train a modern language model from the ground up. Spanning 12 chapters and over 7,500 lines of code, the guide uses straightforward language and extensive annotations to make complex concepts like attention mechanisms, tokenization, and training pipelines accessible to those with no prior machine learning experience. It covers state-of-the-art techniques such as Relative Position Encoding (RoPE), RMSNorm, and SwiGLU, which are fundamental in improving performance and efficiency in language models like ChatGPT and LLaMA. This guide is significant for the AI/ML community as it addresses a common gap in educational resources: balancing depth with accessibility. While many tutorials either skim important details or delve into overly complicated jargon, this guide employs child-friendly analogies alongside comprehensive code examples, ensuring learners understand the underlying principles of Transformers and how they operate. Users will not only learn to implement a language model but also gain insight into the design choices and mathematical foundations behind each component, equipping them with the knowledge to confidently read and understand contemporary ML research.