https://github.com/6deadshot9/potato-diffusion
Potato Diffusion is a hands-on repository that demystifies diffusion models by building them from scratch using PyTorch. Dive into implementing core AI components like VAE, CLIP, and UNet with clean, modular, and easy-to-read code—perfect for learning through doing.
https://github.com/6deadshot9/potato-diffusion
ai diffusion-models generative-ai ml stable-diffusion
Last synced: about 2 months ago
JSON representation
Potato Diffusion is a hands-on repository that demystifies diffusion models by building them from scratch using PyTorch. Dive into implementing core AI components like VAE, CLIP, and UNet with clean, modular, and easy-to-read code—perfect for learning through doing.
- Host: GitHub
- URL: https://github.com/6deadshot9/potato-diffusion
- Owner: 6DEADSHOT9
- License: mit
- Created: 2025-04-02T10:42:54.000Z (about 2 months ago)
- Default Branch: main
- Last Pushed: 2025-04-02T10:52:18.000Z (about 2 months ago)
- Last Synced: 2025-04-02T11:34:22.680Z (about 2 months ago)
- Topics: ai, diffusion-models, generative-ai, ml, stable-diffusion
- Language: Python
- Homepage:
- Size: 0 Bytes
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: LICENSE.md
Awesome Lists containing this project
README
## What is this all about?
Welcome to **Potato Diffusion**—a no-nonsense dive into building a diffusion model from the ground up. This repository is all about implementing the core components—VAE, CLIP, and UNet—using PyTorch, with a focus on simplicity and transparency.
## Why This Matters
- **Learn by Doing**: Build everything from scratch to truly understand how diffusion models work.
- **Core AI Components**: Master the architecture behind VAE, CLIP, and UNet.
- **Clean and Modular**: Code that's easy to read, extend, and experiment with.
## Quick Start
1. Clone the repository:
```bash
git clone https://github.com/your-username/potato-diffusion.git
```
2. Install dependencies:
```bash
cd potato-diffusion && pip install -r requirements.txt
```
3. Run the project:
```bash
python main.py
```
## Contribute
Found an issue or have an idea? Open a pull request and help improve the project.
## License
This project is licensed under the [MIT License](LICENSE).