This repository provides practical knowledge and hands-on experience for LLM engineering and application deployment. It covers LLM training topics including parameter-efficient fine-tuning techniques and distributed training strategies, LLM inference frameworks and optimization methods, model compression techniques such as quantization, pruning, and knowledge distillation, as well as LLM evaluation and alignment techniques. The content appears structured as an educational resource with detailed technical documentation in Chinese.