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Fix optional model in tabular tasks #2018

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Feb 7, 2024
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Co-authored-by: Abubakar Abid <abubakar@huggingface.co>
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Wauplin and abidlabs authored Feb 7, 2024
commit 78a2b7553078b7603d9f6d7ed4490b10c09e1be5
4 changes: 2 additions & 2 deletions src/huggingface_hub/inference/_client.py
Original file line number Diff line number Diff line change
Expand Up @@ -1072,7 +1072,7 @@ def tabular_classification(self, table: Dict[str, Any], *, model: Optional[str]
Set of attributes to classify.
model (`str`, *optional*):
The model to use for the tabular classification task. Can be a model ID hosted on the Hugging Face Hub or a URL to
a deployed Inference Endpoint. If not provided, the default recommended text classification model will be used.
a deployed Inference Endpoint. If not provided, the default recommended tabular classification model will be used.
Defaults to None.

Returns:
Expand Down Expand Up @@ -1117,7 +1117,7 @@ def tabular_regression(self, table: Dict[str, Any], *, model: Optional[str] = No
Set of attributes stored in a table. The attributes used to predict the target can be both numerical and categorical.
model (`str`, *optional*):
The model to use for the tabular regression task. Can be a model ID hosted on the Hugging Face Hub or a URL to
a deployed Inference Endpoint. If not provided, the default recommended text classification model will be used.
a deployed Inference Endpoint. If not provided, the default recommended tabular regression model will be used.
Defaults to None.

Returns:
Expand Down