This repository provides simplified code examples for fine-tuning diffusion models using LoRA (Low-Rank Adaptation), a technique developed by Microsoft to reduce trainable parameters by learning rank-decomposition matrices. It allows AI generation researchers to efficiently customize Stable Diffusion models with fewer computational resources by fine-tuning only the residual weights instead of the entire model. The guide also covers working with safetensors format for model storage.