code: def test_train_load_use_tagger_disjunct_tags(
      self,
      results_base_path,
      tasks_base_path,
      embeddings,
      example_sentence,
  ):
      corpus = flair.datasets.ColumnCorpus(
          data_folder=tasks_base_path / "fashion_disjunct",
          column_format={0: "text", 3: "ner"},
      )
      tag_dictionary = corpus.make_label_dictionary("ner", add_unk=True)
      model = self.build_model(
          embeddings, tag_dictionary, allow_unk_predictions=True
      )
      trainer = ModelTrainer(model, corpus)
  
      trainer.train(
          results_base_path, shuffle=False, **self.training_args
      )
  
      del trainer, model, tag_dictionary, 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])
      del loaded_model
  
file_path: flair/tests/models/test_sequence_tagger.py
imports: import pytest
  import flair
  from flair.embeddings import FlairEmbeddings, WordEmbeddings
  from flair.models import SequenceTagger
  from flair.trainers import ModelTrainer
  from tests.model_test_utils import BaseModelTest
label_desc: Use image node_id 9 for calling the TestSequenceTagger obj's underlying member method code with example usage: obj.test_train_load_use_tagger_disjunct_tags(results_base_path, tasks_base_path, embeddings, example_sentence) without return types