code: def test_train_load_use_tagger_with_trainable_hidden_state(
      self, embeddings, results_base_path, corpus, example_sentence
  ):
      tag_dictionary = corpus.make_label_dictionary(
          "ner", add_unk=False
      )
  
      model = self.build_model(
          embeddings, tag_dictionary, train_initial_hidden_state=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 8 for calling the TestSequenceTagger obj's underlying member method code with example usage: obj.test_train_load_use_tagger_with_trainable_hidden_state(embeddings, results_base_path, corpus, example_sentence) without return types