def _uncast_label_questions_as_classlabels(hf_dataset: "HFDataset", columns: List[str]) -> "HFDataset":
    """Cast the class label features in the Hugging Face dataset as strings.

    Parameters:
        hf_dataset (HFDataset): The Hugging Face dataset to cast.
        columns (List[str]): The names of the columns containing the class label features.

    Returns:
        HFDataset: The Hugging Face dataset with class label features cast as strings.
    """
    for column in columns:
        column = f"{column}.suggestion"
        if column not in hf_dataset.column_names:
            continue
        values = list(hf_dataset.unique(column))
        features = hf_dataset.features.copy()
        features[column] = ClassLabel(names=values)
        hf_dataset = hf_dataset.map(
            function=lambda batch: {column: [values.index(sample) for sample in batch]},
            with_indices=False,
            batched=True,
            input_columns=[column],
            remove_columns=[column],
            features=features,
        )
    return hf_dataset
Cast the class label features in the Hugging Face dataset as strings.

    Parameters:
        hf_dataset (HFDataset): The Hugging Face dataset to cast.
        columns (List[str]): The names of the columns containing the class label features.

    Returns:
        HFDataset: The Hugging Face dataset with class label features cast as strings.
    
argilla/src/argilla/records/_io/_datasets.py