---
library_name: pytorch
tags:
- diffusion
- ddpm
- cifar10
---
# Diffusion final checkpoints

Unconditional and conditional DDPM training artifacts for CIFAR-10, using
custom UNet architectures with attention and EMA.

Only the final unconditional and conditional checkpoints are published:

- `ddpm_with_attention_ema/checkpoints/ddpm_final.pt`
- `conditional_ddpm_with_attention_ema/checkpoints/conditional_ddpm_final.pt`

Each file is about 3.11 GiB, about 6.2 GiB combined. Intermediate checkpoints,
sample images, and training history CSV files are not published. The original
full final checkpoints contain model, EMA model, optimizer, scheduler, epoch,
and loss state. Use `ema_model_state_dict` for EMA inference weights, with the
matching custom architectures from the code repository.

Download the repository contents into `Unet/outputs` in the code project.

## Code

https://github.com/wangwenbinw/Diffusion