| 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 | |