docstr: The function takes in a list of strings and returns a list of predictions
  
  Args:
    text (Union[List[str], str]): The text to be classified.
    as_argilla_records (bool): If True, the prediction will be returned as an Argilla record. If
  False, the prediction will be returned as a string. Defaults to True
  
  Returns:
    A list of predictions
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code: def predict(
      self,
      text: Union[List[str], str],
      as_argilla_records: bool = True,
      **kwargs,
  ):
      """
      The function takes in a list of strings and returns a list of predictions
  
      Args:
        text (Union[List[str], str]): The text to be classified.
        as_argilla_records (bool): If True, the prediction will be returned as an Argilla record. If
      False, the prediction will be returned as a string. Defaults to True
  
      Returns:
        A list of predictions
      """
      self._logger.error(
          f"Use ArgillaTrainer(name={self._name}, workspace={self._workspace}, framework='transformers', model='my_model_name') for inference via `.predict()`."
      )
  
imports: import logging
  import os
  from typing import List, Optional, Union
  from uuid import uuid4
  from datasets import DatasetDict
  from argilla.client.models import TextClassificationRecord, TokenClassificationRecord
  from argilla.training.base import ArgillaTrainerSkeleton
  from argilla.utils.dependency import require_dependencies
label_desc: Use image node_id 8 for calling the ArgillaAutoTrainTrainer obj's underlying member method code with example usage: obj.predict(text, as_argilla_records) without return types