infocusp/diffusion_models
Minimal standalone example of diffusion model
This project provides a clear, step-by-step example for understanding how diffusion models work. It takes you through the mathematical principles and corresponding code, showing how an image can be progressively noised (forward process) and then reconstructed (reverse process). It's designed for machine learning practitioners, researchers, and students who want to grasp the core mechanics of these generative AI models.
163 stars. No commits in the last 6 months.
Use this if you are a machine learning student or researcher looking for a straightforward, explained example to learn the fundamental concepts of diffusion models.
Not ideal if you are looking for a pre-trained model to generate new images or a robust library for a production application.
Stars
163
Forks
17
Language
Jupyter Notebook
License
MIT
Category
Last pushed
Jun 04, 2022
Commits (30d)
0
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