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ddpm-mnist

Unconditional Image Generation
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metadata
license: mit
tags:
  - pytorch
  - diffusers
  - unconditional-image-generation
  - diffusion-models-class
datasets:
  - mnist
library_name: diffusers
pipeline_tag: unconditional-image-generation
thumbnail: https://upload.wikimedia.org/wikipedia/commons/f/f7/MnistExamplesModified.png

Unconditional MNIST DDPM

Description

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.

Usage 

from diffusers import DDPMPipeline

pipeline = DDPMPipeline.from_pretrained('1aurent/ddpm-mnist')
image = pipeline().images[0]
image