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

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 only stores and executes the generated program, so this is not a claim that the transformer itself run