---
title: Guohua-Diffusion
canonical_url: "https://www.modelscope.cn/models/langboat/Guohua-Diffusion"
md_url: "https://www.modelscope.cn/models/langboat/Guohua-Diffusion.md"
repository: langboat/Guohua-Diffusion
chinese_name: "国画Diffusion模型"
last_updated: 2023-02-27
license: creativeml-openrail-m
pipeline_tag: text-to-image-synthesis
tasks:
  - text-to-image-synthesis
library_name:
  - lora
  - pytorch
frameworks:
  - pytorch
downloads: 38151
stars: 72
tags:
  - stable-diffusion
  - text-to-image
---

# Guohua-Diffusion

> Guohua-Diffusion - langboat 在 ModelScope 开源的模型。这是在国画上训练的微调Stable Diffusion模型

langboat/Guohua-Diffusion 是 ModelScope 魔搭社区上的text-to-image-synthesis模型，采用 creativeml-openrail-m 许可。

- **Repository**: langboat/Guohua-Diffusion
- **License**: creativeml-openrail-m
- **Tasks**: text-to-image-synthesis
- **Tags**: stable-diffusion, text-to-image
- **Downloads**: 38151
- **Stars**: 72
- **Last updated**: 2023-02-27

Source: https://www.modelscope.cn/models/langboat/Guohua-Diffusion

---

---
# 国画Diffusion
This is the fine-tuned Stable Diffusion model trained on traditional Chinese paintings.
这是在国画上训练的微调Stable Diffusion模型。
Use **guohua style** in your prompts for the effect.

## 示例图片
![example1](Untitled-1.png)
![example2](Untitled-3.png)

## 如何使用
```python
from modelscope.utils.constant import Tasks
from modelscope.pipelines import pipeline
import cv2

pipe = pipeline(task=Tasks.text_to_image_synthesis, 
                model='langboat/Guohua-Diffusion',
                model_revision='v1.0')

prompt = 'The Godfather poster in guohua style'
output = pipe({'text': prompt})
cv2.imwrite('result.png', output['output_imgs'][0])

```

#### Diffusers
该模型可以像任何其他Stable Diffusion模型一样使用。
This model can be used just like any other Stable Diffusion model.