A Microscopic Study of Decimal Parity in a Tiny Causal Transformer

A microscopic study of a tiny GPT-style transformer learning decimal parity. Despite using distributed internal computations rather than a simple last-digit lookup, the 217k-parameter model achieves 99.97% accuracy and robust length generalization on even/odd classification.