'How can I retrive the model.pkl in the experiment in Databricks
I want to retrieve the pickle off my trained model, which I know is in the run file inside my experiments in Databricks.
It seems that the mlflow.pyfunc.load_model can only do the predict method.
There is an option to directly access the pickle?
I also tried to use the path in the run using the pickle.load(path) (example of path: dbfs:/databricks/mlflow-tracking/20526156406/92f3ec23bf614c9d934dd0195/artifacts/model/model.pkl).
Solution 1:[1]
Use the frmwk's native load_model() method (e.g. sklearn.load_model()) or download_artifacts()
Sources
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Source: Stack Overflow
| Solution | Source |
|---|---|
| Solution 1 | Andre |