# [Denoising Diffusion Probabilistic Models (DDPM)](https://nn.labml.ai/diffusion/ddpm/index.html)

This is a [PyTorch](https://pytorch.org) implementation/tutorial of the paper
[Denoising Diffusion Probabilistic Models](https://papers.labml.ai/paper/2006.11239).

In simple terms, we get an image from data and add noise step by step.
Then We train a model to predict that noise at each step and use the model to
generate images.

Here is the [UNet model](https://nn.labml.ai/diffusion/ddpm/unet.html) that predicts the noise and
[training code](https://nn.labml.ai/diffusion/ddpm/experiment.html).
[This file](https://nn.labml.ai/diffusion/ddpm/evaluate.html) can generate samples and interpolations
from a trained model.

[![View Run](https://img.shields.io/badge/labml-experiment-brightgreen)](https://app.labml.ai/run/a44333ea251411ec8007d1a1762ed686)