Andre Mesarovic comments

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                                            Andre Mesarovic

[Proposal] MLflow Pipelines (previously named as MLX)

Are there any code examples? For notebooks (Jupyter and Databricks) and non-notebook IDE-based code.

Save a different storage

Only Python file system is supported now. You can always download to your laptop and then copy the folder to the cloud. However you can export to blob storage when...

Save a different storage

Not sure what you mean by "saving the local data " and "download an entire folder". The tool exports the entire artifacts folder recursively and then imports it. This all...

Cannot clone in databricks

https://github.com/amesar/mlflow-export-import has been deprecated and move to https://github.com/mlflow/mlflow-export-import. Please raise this issue there.

https://github.com/amesar/mlflow-export-import#databricks-export-examples [https://opengraph.githubassets.com/5f7bcec87702c4eecf4b943e4e45ef3297ca308edcfe01d0f5412273a18bdad1/amesar/mlflow-export-import] amesar/mlflow-export-import: Export and import MLflow experiments, runs or registered models - GitHub Setup. Supports python 3.7.6 or above. Console scripts. Python console scripts (such as export-run, import-run) are...

Importing the exported model with --delete-model set to True removes all history and the imported model is also not able serve without manually registering it again

1. Deletes all the previous history for this model That is what it is supposed to do. Check the documentation with --help. 2. Does not show the model type... Cannot...

Importing the exported model with --delete-model set to True removes all history and the imported model is also not able serve without manually registering it again

Without the source code and reproducible steps, sort of hard to troubleshoot.

Importing the exported model with --delete-model set to True removes all history and the imported model is also not able serve without manually registering it again

I don't work on Windows. Since export is successful, send me a zip file of the exported model in order to debug.

Importing the exported model with --delete-model set to True removes all history and the imported model is also not able serve without manually registering it again

Don't see a zip file.

Importing the exported model with --delete-model set to True removes all history and the imported model is also not able serve without manually registering it again

I have successfully imported the model. When I try to pyfunc.load_model I am getting a "valueError: unsupported pickle protocol: 5". I'd suggest you use flavor-specific logging such as sklearn.log_model instead...