ReLuckyLucy/Diffusion_Mnist
基于MNIST数据集，从零构建diffusion扩散模型
This project helps machine learning practitioners learn how to build a diffusion model from scratch. It takes the well-known MNIST dataset of handwritten digits and guides you through adding noise to the images, constructing a UNet model, training it, and sampling new images. The intended user is a student or researcher in machine learning looking to understand the fundamentals of diffusion models.
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Use this if you are a machine learning student or researcher who wants a hands-on guide to building and understanding diffusion models using a simple, well-understood dataset.
Not ideal if you are looking for a pre-trained model for complex image generation tasks or a high-performance diffusion model for production use.
Stars
7
Forks
1
Language
Python
License
MIT
Category
Last pushed
Apr 09, 2025
Commits (30d)
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