sayakpaul/nanoDiT
Just another reasonably minimal repo for class-conditional training of pixel-space diffusion transformers.
This educational repository helps you learn how to generate images based on specific categories. You provide image data, and it outputs new, synthetic images that match the characteristics of the categories you've trained it on. It's designed for students or researchers who want to understand the inner workings of modern image generation techniques.
146 stars. No commits in the last 6 months.
Use this if you are a student or researcher keen on understanding and experimenting with class-conditional image generation using diffusion transformers and rectified flows.
Not ideal if you need a production-ready image generation tool or a high-performance solution for large-scale datasets.
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146
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18
Language
Python
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Last pushed
May 29, 2025
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