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---
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/)
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