Kei18/tiny-tiny-diffusion

minimal diffusion model for self-study

24
/ 100
Experimental

This project helps machine learning practitioners or students understand the core mechanics of diffusion models by providing a simplified, hands-on example. It takes a small dataset of 2D shapes (like a dinosaur or a cat) and demonstrates how a diffusion model can learn to reconstruct these shapes from random noise. The end-user is anyone looking to grasp the fundamental concepts of generative AI through a practical, lightweight implementation.

No commits in the last 6 months.

Use this if you are an aspiring machine learning engineer or researcher trying to learn how diffusion models work through a minimal, runnable code example.

Not ideal if you need a production-ready generative AI tool or want to train high-resolution image generation models on complex datasets.

generative-ai machine-learning-education diffusion-models model-training algorithm-understanding
No License Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 7 / 25
Maturity 8 / 25
Community 9 / 25

How are scores calculated?

Stars

28

Forks

3

Language

Python

License

Last pushed

Jul 08, 2023

Commits (30d)

0

Get this data via API

curl "https://pt-edge.onrender.com/api/v1/quality/diffusion/Kei18/tiny-tiny-diffusion"

Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.