class_docstr: Transformers handler class for sequence, token classification and question answering.
docstr: Post Process Function converts the predicted response into Torchserve readable format.
  Args:
      inference_output (list): It contains the predicted response of the input text.
  Returns:
      (list): Returns a list of the Predictions and Explanations.
docstr_tok: ["Post","Process","Function","converts","the","predicted","response","into","Torchserve","readable","format",".","Args",":","inference_output","(","list",")",":","It","contains","the","predicted","response","of","the","input","text",".","Returns",":","(","list",")",":","Returns","a","list","of","the","Predictions","and","Explanations","."]
code: def postprocess(self, inference_output):
      """Post Process Function converts the predicted response into Torchserve readable format.
      Args:
          inference_output (list): It contains the predicted response of the input text.
      Returns:
          (list): Returns a list of the Predictions and Explanations.
      """
      return inference_output
  
imports: import ast
  import json
  import logging
  import os
  from abc import ABC
  import torch
  import transformers
  from captum.attr import LayerIntegratedGradients
  from transformers import AutoModelForCausalLM, AutoModelForQuestionAnswering, AutoModelForSequenceClassification, AutoModelForTokenClassification, AutoTokenizer, GPT2TokenizerFast
  from ts.torch_handler.base_handler import BaseHandler
label_desc: Use image node_id 5 for calling the TransformersSeqClassifierHandler obj's underlying member method code with example usage: obj.postprocess(inference_output) and returns: inference_output