Resolved! Can I save MLflow artifacts to locations other than the dbfs?
The default location or MLflow artifacts is on dbfs, but I would like to save my models to an alternative location. Is this supported, and if it is how can I accomplish it?
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You could mount an s3 bucket in the workspace and save your model using the mounts DBFS path For e.gmodelpath = "/dbfs/my-s3-bucket/model-%f-%f" % (alpha, l1_ratio) mlflow.sklearn.save_model(lr, modelpath)
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