Diffusion models have shown great promise in generating high-quality samples in various domains. In this project, we utilize a UNet transformer-based diffusion model to generate samples of handwritten digits. The process involves:
Setting up the model and loading pre-trained weights.
Generating samples for each digit.
Creating a GIF to visualize the generated samples.
