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One alternative to loading models in .py scripts is making use of joblib's dump() and load() methods for pipelines. https://joblib.readthedocs.io/en/latest/generated/joblib.dum....

That way, if you put your classifiers in joblib pipelines, once you're done with fitting steps you can just export your trained classifier with:

    joblib.dump(pipe, "trained_classifier.dump")
And resume your work with:

    joblib.load("trained_classifier.dump")
Considering this works for any Python object, a lot of heavy lifting can be exported for later (swift) use this way.



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