This repository features a generative AI image generator designed to run on the RP2350 microcontroller (Raspberry Pi Pico 2). The model uses a latent flow diffusion transformer (DiT) architecture, similar to Flux, but scaled down significantly with only 1.7 or 2.9 million parameters—thousands of times smaller than typical local diffusion models. It can generate $128 times 128$ RGB images of human faces in approximately 5-20 seconds and supports conditional generation for five classes based on gender, smile, and neutral expressions.
- The model architecture includes a VAE decoder and a DiT component.
- Hardware output can be displayed via a VGA monitor or streamed over USB.
- Includes an int8 pipeline involving calibration, distillation-QAT (Quantization-Aware Training), and folding.
- Two variants are provided: a high-quality flagship model and a faster build version.
- The model architecture includes a VAE decoder and a DiT component.
- Hardware output can be displayed via a VGA monitor or streamed over USB.
- Includes an int8 pipeline involving calibration, distillation-QAT (Quantization-Aware Training), and folding.
- Two variants are provided: a high-quality flagship model and a faster build version.
