metadata
license: mit
datasets:
- huggan/anime-faces
pipeline_tag: unconditional-image-generation
tags:
- art
ddpm-anime-faces-64
ddpm-anime-faces-64 is an educational project for introducing the training and sampling processes of DDPM and DDIM models. The model is trained on huggan/anime-faces dataset.
Training Arguments
| Argument | Value |
|---|---|
| image_size | 64 |
| train_batch_size | 16 |
| eval_batch_size | 16 |
| num_epochs | 50 |
| gradient_accumulation_steps | 1 |
| learning_rate | 1e-4 |
| lr_warmup_steps | 500 |
| mixed_precision | "fp16" |
For training code, please refer to this link.
Inference
This project aims to implement DDPM from scratch, so DDPMScheduler is not used. Instead, I use only UNet2DModel and implement a simple scheduler myself.
Please refer to sampling_ddpm.py and sampling_ddim.py for detailed usages.