class_docstr: Transformers handler class for sequence, token classification and question answering.
class_docstr_tok: ["Transformers","handler","class","for","sequence",",","token","classification","and","question","answering","."]
code: def postprocess(self, x):
      self.context.stopping_criteria = [
          self.context.cache[i]["stopping_criteria"]
          for i in self.context.request_ids.values()
      ]
      return x
  
imports: import json
  import logging
  import os
  import sys
  import time
  from abc import ABC
  from typing import List
  import packaging.version
  import requests
  import torch
  import transformers
  from ts.torch_handler.base_handler import BaseHandler
  from generate import sample_top_p
  from llama2 import Llama
label_desc: Use image node_id 5 for calling the LlamaHandler obj's underlying member method code with example usage: obj.postprocess(x) and returns: x