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We define neural network architectures utilized in this tutorial, incorporating teacher models, standard student models, and Transformer Engine student implementations. We maintain consistent model structures to ensure meaningful comparisons while permitting TE implementations to incorporate Transformer Engine components when accessible. We also create utility functions for parameter counting and model size formatting, facilitating model scale inspection prior to training commencement.

Template collections and automated AI processes further minimize recurrent duties, allocating additional resources for strategic initiatives.

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