scepter

Why we included this project

SCEPTER is a training and inference framework for generative image models, built around the diffusion architectures that most AIGC work relies on today. It handles fine-tuning of Stable Diffusion, SDXL, FLUX, and DiT-based models like PixArt and SD3 in a single codebase, with LoRA and Res-Tuning style efficient tuning, DDP/FSDP distributed training, and checkpoint management. The Gradio-based Studio interface and ComfyUI workflow support let you move from a tuned model to a working image-editing or generation pipeline without assembling separate tools. It also bundles reproducible implementations of methods like SCEdit, ACE, and StyleBooth, so it works as a reference for controllable synthesis and instruction-based editing experiments.