Edit model card

Unconditional MNIST DDPM


This model is a very lightweight UNet2D trained on the MNIST dataset.
This model is unconditional, meaning that you cannot pick which number you'd like to generate.
This model was trained in ~40min on an L4 GPU Google Colab instance. You can see the training logs in the Training metrics tab.

A conditional model is available at 1aurent/ddpm-mnist-conditional, though it is pretty buggy.


from diffusers import DDPMPipeline

pipeline = DDPMPipeline.from_pretrained('1aurent/ddpm-mnist')
image = pipeline().images[0]
Downloads last month
Inference API (serverless) does not yet support diffusers models for this pipeline type.

Dataset used to train 1aurent/ddpm-mnist

Space using 1aurent/ddpm-mnist 1