This repository serves as an LLM treasure box, curating links and references across the full lifecycle of large language model development. It organizes resources into categories spanning algorithm fundamentals (Transformers), training and fine-tuning techniques, alignment methods, inference optimization, data engineering, model compression, evaluation benchmarks, AI infrastructure (chips, CUDA), and LLMOps practices. The collection also includes links to code implementations and explanatory articles.