code: def test_train_load_use_model_multi_label(
      self,
      results_base_path,
      multi_class_corpus,
      embeddings,
      example_sentence,
      multiclass_train_test_sentence,
  ):
      flair.set_seed(123)
      label_dict = multi_class_corpus.make_label_dictionary(
          label_type=self.train_label_type
      )
  
      model = self.build_model(embeddings, label_dict, multi_label=True)
      corpus = self.transform_corpus(model, multi_class_corpus)
  
      trainer = ModelTrainer(model, corpus)
      trainer.train(
          results_base_path,
          mini_batch_size=1,
          max_epochs=5,
          shuffle=False,
          train_with_test=True,
          train_with_dev=True,
      )
  
      model.predict(multiclass_train_test_sentence)
  
      sentence = Sentence("apple tv")
  
      model.predict(sentence)
      for label in self.multiclass_prediction_labels:
          assert label in [
              label.value
              for label in sentence.get_labels(self.train_label_type)
          ], label
  
      for label in sentence.labels:
          print(label)
          assert label.value is not None
          assert 0.0 <= label.score <= 1.0
          assert isinstance(label.score, float)
  
      del trainer, model, multi_class_corpus
      loaded_model = self.model_cls.load(
          results_base_path / "final-model.pt"
      )
  
      loaded_model.predict(example_sentence)
      loaded_model.predict([example_sentence, self.empty_sentence])
      loaded_model.predict([self.empty_sentence])
  
imports: from typing import Any, Dict, List, Optional, Type
  import pytest
  import flair
  from flair.data import Dictionary, Sentence
  from flair.embeddings import TransformerEmbeddings
  from flair.models import FewshotClassifier
  from flair.nn import Model
  from flair.trainers import ModelTrainer
label_desc: Use image node_id 19 for calling the BaseModelTest obj's underlying member method code with example usage: obj.test_train_load_use_model_multi_label(results_base_path, multi_class_corpus, embeddings, example_sentence, multiclass_train_test_sentence) without return types