I built my 'first' flow matching image generator, here's what I learned [P]

Summary

Today I put out my first flow matching image generation model! This is a toy example trained on a 2024 MPS Macbook Pro using a small sample of images—specifically, the Apple emoji library and their text labels. Because of this, it’s not a massive model (clocking in at ~4.7 million parameters), but it was an incredible learning experience. My original approach (which failed): I initially tried taking the emoji images, converting them to grayscale, and using an extremely basic CNN to expand the gr

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