yuanchenyang/smalldiffusion
Simple and readable code for training and sampling from diffusion models
This is for machine learning researchers and practitioners who want to rapidly experiment with diffusion models. It helps you quickly set up, train, and sample from various diffusion models, whether you're working with simple datasets or state-of-the-art models like Stable Diffusion. You input your dataset and chosen model/schedule parameters, and it outputs generated samples and insights into model performance.
715 stars. No commits in the last 6 months. Available on PyPI.
Use this if you are a machine learning researcher or engineer looking for a clear, concise, and flexible codebase to build, train, and test new diffusion models or sampling techniques.
Not ideal if you are looking for a high-level API to simply use existing, pre-trained diffusion models without needing to customize or understand their underlying mechanics.
Stars
715
Forks
55
Language
Python
License
MIT
Category
Last pushed
Jun 14, 2025
Commits (30d)
0
Dependencies
6
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