class_docstr: Multi choice question finetune model.
  
  :param config: A :py:class:`finetune.config.Settings` object or None (for default config).
code: def _target_model(
      self,
      *,
      config,
      featurizer_state,
      targets,
      n_outputs,
      train=False,
      reuse=None,
      **kwargs,
  ):
      return multi_choice_question(
          hidden=featurizer_state["features"],
          targets=targets,
          n_targets=n_outputs,
          config=config,
          train=train,
          reuse=reuse,
          **kwargs,
      )
  
imports: import numpy
  from finetune.base import BaseModel
  from finetune.input_pipeline import BasePipeline
  from finetune.encoding.input_encoder import EncodedOutput
  from finetune.encoding.target_encoders import IDEncoder
  import tensorflow
  from finetune.nn.target_blocks import multi_choice_question
  from finetune.util import list_transpose
  from finetune.encoding.input_encoder import tokenize_context
  from finetune.model import PredictMode
label_desc: Use image node_id 5 for calling the MultipleChoice obj's underlying member method code with example usage: obj._target_model() and returns: multi_choice_question