code: def load_model(self):
      with open(IntentExtractionApi.pretrained_model_info, "rb") as fp:
          model_info = pickle.load(fp)
      self.model_type = model_info["type"]
      self.word_vocab = model_info["word_vocab"]
      self.tags_vocab = {
          v: k for k, v in model_info["tags_vocab"].items()
      }
      if self.model_type == "mtl":
          self.char_vocab = model_info["char_vocab"]
          self.intent_vocab = {
              v: k for k, v in model_info["intent_vocab"].items()
          }
          model = MultiTaskIntentModel()
      else:
          model = Seq2SeqIntentModel()
      model.load(self.pretrained_model)
      self.model = model
  
file_path: nlp-architect/nlp_architect/api/intent_extraction_api.py
imports: import numpy
  import pickle
  from os import makedirs, path, sys
  from nlp_architect.api.abstract_api import AbstractApi
  from nlp_architect.models.intent_extraction import MultiTaskIntentModel, Seq2SeqIntentModel
  from nlp_architect import LIBRARY_OUT
  from nlp_architect.utils.generic import pad_sentences
  from nlp_architect.utils.io import download_unlicensed_file
  from nlp_architect.utils.text import SpacyInstance, bio_to_spans
label_desc: Use image node_id 8 for calling the IntentExtractionApi obj's underlying member method code with example usage: obj.load_model() without return types