code: def load_model(self, model_name, model_path, model_type):
      logger.info(
          ">> Loading HF model " + model_name + " from " + model_path
      )
      self.type = model_type
      self.name = model_name
      self.tokenizer = AutoTokenizer.from_pretrained(
          model_path, use_fast=True
      )
      self.model = TFAutoModelForQuestionAnswering.from_pretrained(
          model_path, from_pt=True
      )
  
file_path: neuralqa/neuralqa/reader/reader.py
imports: import tensorflow
  import numpy
  from transformers import AutoTokenizer, TFAutoModelForQuestionAnswering
  import time
  import logging
label_desc: Use image node_id 2 for calling the Reader obj's underlying member method code with example usage: obj.load_model(model_name, model_path, model_type) without return types