code: def load_data(
      self,
      inputs: List[str],
      targets: Optional[List[Any]] = None,
      target_formatter: Optional[TargetFormatter] = None,
  ) -> Dataset:
      if targets is not None:
          hf_dataset = Dataset.from_dict(
              {DataKeys.INPUT: inputs, DataKeys.TARGET: targets}
          )
      else:
          hf_dataset = Dataset.from_dict({DataKeys.INPUT: inputs})
      return super().load_data(
          hf_dataset,
          DataKeys.INPUT,
          DataKeys.TARGET,
          target_formatter=target_formatter,
      )
  
imports: from functools import partial
  from typing import Any, Dict, List, Optional, Union
  import pandas
  from flash.core.data.io.classification_input import ClassificationInputMixin
  from flash.core.data.io.input import DataKeys, Input
  from flash.core.data.utilities.classification import MultiBinaryTargetFormatter, TargetFormatter
  from flash.core.data.utilities.loading import load_data_frame
  from flash.core.data.utilities.paths import PATH_TYPE
  from flash.core.utilities.imports import _TOPIC_TEXT_AVAILABLE, requires
label_desc: Use image node_id 1 for calling the TextClassificationListInput obj's underlying member method code with example usage: obj.load_data(inputs, targets, target_formatter) and returns: super