ckg/mnist-for-diffusion

MNIST for Diffusion

Training a diffusion model from scratch is pretty cool, why not do so with the canonical "hello world" dataset of computer vision? This dataset matches the sample dataset from this text_to_image.py diffusion tutorial. Specifying ckg/mnist-for-diffusion ought get you off to the races.

This dataset contains two copies of the original MNIST train & test sets. The first half of the dataset contains MNIST images with the string-ified class id (i.e: "1") and the second half has the class id mapped to a natural language name (i.e: "one"). This little data augmentation doubles the number of samples and should result in interesting behavior if you train a U-Net from scratch whilst using a frozen, pre-trained text-encoder!

Thank you LeCun & Cortes for making this dataset available.