append has to allocate one. Because it doesn’t know how big the
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The model does the work, not the code. The inference code should be generic autoregressive decoding that would work with any transformer checkpoint. If your generation loop contains addition-specific logic — manually pairing digits, threading carry state, indexing into specific positions — then the Python code is solving the problem, not the model.
In short: if you can swap in a different set of weights and use the exact same inference code for a different task, your setup is legitimate. If the inference code is inseparable from the algorithm, it's not.
I don’t do much gaming, but I recently added a PC gaming layer with WASD keys in the same positions as the arrow keys are on the navigation layer. I did my best to optimize this layer for gaming with my limited experience.