Transformers & LLMs cheatsheet

Transformers & LLMs cheatsheet is an educational repository focused on transformers, large language models, and modern generative AI architectures based on Stanford CME 295 coursework. The project compiles structured notes, mathematical explanations, diagrams, and implementation references covering transformer internals, attention mechanisms, tokenization, training pipelines, and inference strategies. It is designed to help students and practitioners understand the technical foundations behind contemporary AI systems such as GPT-style models and multimodal architectures. The repository emphasizes conceptual clarity while still addressing practical engineering considerations involved in training and scaling transformer models. It serves as both a study companion and a technical reference for researchers exploring the rapidly evolving LLM ecosystem.