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Shrinking gigabyte sized scikit-learn models for deployment

Description

We present an open source library to shrink pickled scikit-learn and lightgbm models. We will provide insights of how pickling ML models work and how to improve the disk representation. With this approach, we can reduce the deployment size of machine learning applications up to 6x.

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