---
license: mit
tags:
- pytorch
- diffusers
- unconditional-image-generation
- diffusion-models-class
datasets:
- Norod78/Vintage-Faces-FFHQAligned
---

# English Version

## Example Fine-Tuned Model for learning diffusion model

My first fintuning model through python script

base model: google/ddpm-celebahq-256

fine-tuning dataset: vintageface

> The loss is not very stable, and the output is not very satisfactory.
> But since it's a study case, you can't ask for too much.


![image/png](https://cdn-uploads.huggingface.co/production/uploads/6462500d2538819c729dc355/QF-nZ18Q251cAiA4Ksi9O.png)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6462500d2538819c729dc355/gkqTtkcIwConyJJaQU4zi.png)

### Usage

```python
from diffusers import DDPMPipeline

pipeline = DDPMPipeline.from_pretrained('Chilli-b/my-finetuned-model-celebahq-on-VintageFaces-4epochs')
image = pipeline().images[0]
image
```

# 中文版

## 学习扩散模型时训练的微调模型

这是我第一个微调模型，也是第一个通过 Python 脚本进行训练的微调模型。

基底模型：google/ddpm-celebahq-256

微调数据集：Norod78/Vintage-Faces-FFHQAligned

> loss 不是很稳定，输出结果也不太令人满意。
> 不过既然是学习案例，那也不能要求太多。

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6462500d2538819c729dc355/QF-nZ18Q251cAiA4Ksi9O.png)

![image/png](https://cdn-uploads.huggingface.co/production/uploads/6462500d2538819c729dc355/gkqTtkcIwConyJJaQU4zi.png)

### 模型使用

```python
from diffusers import DDPMPipeline

pipeline = DDPMPipeline.from_pretrained('Chilli-b/my-finetuned-model-celebahq-on-VintageFaces-4epochs')
image = pipeline().images[0]
image
```