This post explains the concept of Low-Rank Adaptation (LoRA) in Stable Diffusion, a lightweight training technique for fine-tuning large language and diffusion models. LoRA reduces the number of trainable parameters, resulting in faster training times and smaller file sizes. It is compared to checkpoint models and Textual Inversions. The post also provides examples of different types of LoRA models.
