docstr: Define the output names as tokens.
  
  :param inputs: The inputs to the model.
  :type inputs: list[str]
  :return: The output names as the decoded tokens.
  :rtype: list[str]
docstr_tok: ["Define","the","output","names","as","tokens",".",":","param","inputs",":","The","inputs","to","the","model",".",":","type","inputs",":","list","[","str","]",":","return",":","The","output","names","as","the","decoded","tokens",".",":","rtype",":","list","[","str","]"]
code: def output_names(self, inputs):
      """Define the output names as tokens.
  
      :param inputs: The inputs to the model.
      :type inputs: list[str]
      :return: The output names as the decoded tokens.
      :rtype: list[str]
      """
      question, context = inputs.split(SEP)
      d = self._qa_model.tokenizer(question, context)
      return [
          self._qa_model.tokenizer.decode([id]) for id in d["input_ids"]
      ]
  
file_path: responsible-ai-toolbox/responsibleai_text/responsibleai_text/utils/question_answering.py
imports: import logging
  from responsibleai_text.common.constants import Tokens
label_desc: Use image node_id 5 for calling the QAPredictor obj's underlying member method code with example usage: obj.output_names(inputs) and returns: unknown