Comments (2)
@mlflow/mlflow-team Please assign a maintainer and start triaging this issue.
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I think I've found the issue: from the xgboost.core.Booster documentation of the save_model() method, only JSON/UBC are supported.
def save_model(self, fname: Union[str, os.PathLike]) -> None:
"""Save the model to a file.
The model is saved in an XGBoost internal format which is universal among the
various XGBoost interfaces. Auxiliary attributes of the Python Booster object
(such as feature_names) will not be saved when using binary format. To save
those attributes, use JSON/UBJ instead. See :doc:`Model IO
</tutorials/saving_model>` for more info.
.. code-block:: python
model.save_model("model.json")
# or
model.save_model("model.ubj")
Parameters
----------
fname :
Output file name
"""
Should we change the default file format used by mlflow.xgboost.save_model() or mlflow.xgboost.log_model() ?
I've tried to replace the default value of model_format parameter in mlflow.xgboost.init.py from 'xgb' to 'json' and the code provided by @ShivKJ works.
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