code: def get_predictor_model(cls):
      # print(cls.searching_all_files(PATH))
      # Get model predictor
      if cls.model is None:
          with open(os.path.join(PATH, "model_config.json")) as f:
              model_config = json.load(f)
  
          predictor = BertClassificationPredictor(
              os.path.join(PATH, "model_out"),
              label_path=PATH,
              multi_label=bool(model_config["multi_label"]),
              model_type=model_config["model_type"],
              do_lower_case=bool(model_config["do_lower_case"]),
          )
          cls.model = predictor
  
      return cls.model
  
file_path: fast-bert/container_t5/t5/predictor.py
imports: import os
  import json
  import pickle
  import sys
  import signal
  import traceback
  import re
  import flask
  import torch
  from fast_bert.prediction import BertClassificationPredictor
  from fast_bert.utils.spellcheck import BingSpellCheck
  from pathlib import Path
  import warnings
label_desc: Use image node_id 1 for calling the ScoringService obj's underlying member method code with example usage: obj.get_predictor_model(cls) and returns: cls