metadata
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.ptconditional_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.