Scalable machine learning models for predicting quantum transport in disordered 2D hexagonal materials

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Here's a complete synchronous pipeline — compression, transformation, and consumption with zero async overhead:

The converter supports all model types via the --model flag:

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because POSIX has a function for creating a stack)

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