bot66/MNISTDiffusion
Implement a MNIST(also minimal) version of denoising diffusion probabilistic model from scratch.The model only has 4.55MB.
This project helps machine learning researchers and students understand and experiment with denoising diffusion probabilistic models on a very small scale. It takes noisy image data and learns to generate clear, new images, providing a hands-on way to see how diffusion models work without requiring significant computational resources. The output is a functional, lightweight model capable of generating digits.
143 stars. No commits in the last 6 months.
Use this if you are learning about diffusion models and want to train a basic, functional version quickly and efficiently on simple image data.
Not ideal if you need to generate high-resolution images or work with complex datasets beyond basic digits.
Stars
143
Forks
28
Language
Python
License
MIT
Category
Last pushed
Dec 09, 2022
Commits (30d)
0
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