#transformer-based diffusion models

This PyTorch-based implementation enhances diffusion generative models with a novel hourglass diffusion transformer and improved sampling algorithms. It supports multi-GPU setups and offers features like CLIP-guided sampling, adaptive step size control, and hierarchical transformer models. The project also provides tools for efficient training and performance evaluation, emphasizing PyTorch's capabilities.