---
title: stable-diffusion-super-res
canonical_url: "https://www.modelscope.cn/models/lambda-ai/stable-diffusion-super-res"
md_url: "https://www.modelscope.cn/models/lambda-ai/stable-diffusion-super-res.md"
repository: lambda-ai/stable-diffusion-super-res
last_updated: 2026-04-07
license: openrail
library_name:
  - pytorch
frameworks:
  - pytorch
downloads: 6
stars: 0
---

# stable-diffusion-super-res

> stable-diffusion-super-res - lambda-ai 在 ModelScope 开源的模型。I fine tuned a version of Stable Diffusion 1.4 for the task of super-resolution, you can find the trained model on huggingface hub and can run a gradio demo as follows:

lambda-ai/stable-diffusion-super-res 是 ModelScope 魔搭社区上的机器学习模型，采用 openrail 许可。

- **Repository**: lambda-ai/stable-diffusion-super-res
- **License**: openrail
- **Downloads**: 6
- **Stars**: 0
- **Last updated**: 2026-04-07

Source: https://www.modelscope.cn/models/lambda-ai/stable-diffusion-super-res

---

## Super Resolution

I fine tuned a version of Stable Diffusion 1.4 for the task of super-resolution, you can find the [trained model on huggingface hub](https://huggingface.co/lambdalabs/stable-diffusion-super-res) and can run a gradio demo as follows:

```bash
git clone https://github.com/justinpinkney/stable-diffusion.git
cd stable-diffusion
python -m venv .venv --prompt sd
. .venv/bin/activate
pip install -U pip
pip install -r requirements.txt
python scripts/gradio_superres.py
```

Note since I trained this model there is now an 'official' super res model for Stable Diffusion 2 which you might prefer to use.

Trained by [Justin Pinkney](https://www.justinpinkney.com/) ([@Buntworthy](https://twitter.com/Buntworthy)) at [Lambda Labs](https://lambdalabs.com/).