I trained an 825k-parameter model to generate drawing programs that execute exactly on an RP2040 [P]

Excerpt

I’ve been working on a small research project about whether sub-million-parameter models can learn to generate executable drawing programs for constrained hardware. The current system is an 825k-parameter autoregressive transformer which generates ~100 bytes of drawing bytecode rather than pixels. The bytecode is then transferred to a Raspberry Pi Pico, where a small fixed-point virtual machine executes it and streams the resulting geometry back over UART. The model runs on the host. The Pico on