---
language: en
license: apache-2.0
library_name: diffusers
tags: []
datasets: huggan/selfie2anime
metrics: []
---

<!-- This model card has been generated automatically according to the information the training script had access to. You
should probably proofread and complete it, then remove this comment. -->

# ddpm-ema-anime-128

## Model description

This diffusion model is trained with the [🤗 Diffusers](https://github.com/huggingface/diffusers) library 
on the `huggan/selfie2anime` dataset.

## Intended uses & limitations

#### How to use

```python
from diffusers import DDPMPipeline

model_id = "mrm8488/ddpm-ema-anime-128"

# load model and scheduler
pipeline = DDPMPipeline.from_pretrained(model_id)

# run pipeline in inference 
image = pipeline()["sample"]

# save image
image[0].save("anime_face.png")
```

#### Limitations and bias

[TODO: provide examples of latent issues and potential remediations]

## Training data

[TODO: describe the data used to train the model]

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0001
- train_batch_size: 32
- eval_batch_size: 32
- gradient_accumulation_steps: 1
- optimizer: AdamW with betas=(0.95, 0.999), weight_decay=1e-06 and epsilon=1e-08
- lr_scheduler: cosine
- lr_warmup_steps: 500
- ema_inv_gamma: 1.0
- ema_inv_gamma: 0.75
- ema_inv_gamma: 0.9999
- mixed_precision: fp16

### Training results

📈 [TensorBoard logs](https://huggingface.co/mrm8488/ddpm-ema-anime-64/tensorboard?#scalars)

> Created by [Manuel Romero/@mrm8488](https://twitter.com/mrm8488) with the support of [Q Blocks](https://www.qblocks.cloud/)