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Rank-1 linear, factorized embed, sparse gate, param-free norm
，详情可参考safew官方版本下载
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.，更多细节参见heLLoword翻译官方下载
Step 2: If the Generative Language API is enabled, audit your API keys.
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