The model must be autoregressive. It receives a token sequence as input and predicts the next token. Output digits are generated one at a time, with each new token fed back as input for predicting the next. The carry propagation must emerge from this autoregressive process — not from explicit state variables passed between steps in Python.
Uniform regions (solid backgrounds, smooth gradients) get stored as large blocks. Detailed regions (edges, textures) get subdivided into smaller blocks. You end up with a compressed representation that preserves detail where it exists and simplifies where it can.
В России ответили на имитирующие высадку на Украине учения НАТО18:04，更多细节参见51吃瓜
[사설]계엄 때보다 낮은 지지율 17%… 국힘의 존재 이유를 묻는 민심
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