This repository provides an unofficial implementation of BK-SDM paper methods to create compressed Stable Diffusion models through knowledge distillation. It trains a smaller student U-net to mimic a larger teacher model’s noise predictions, reducing model size by approximately 50% while preserving image generation quality. The training uses Realistic Vision’s U-net as the teacher model and the LAION-art dataset with improved captions for training data.