code: def test_setfit_train(dataset_text_classification):
      trainer = ArgillaTrainer(
          name=dataset_text_classification,
          model=MODEL,
          framework=FRAMEWORK,
      )
      output_dir = "tmp_setfit_train"
      trainer.update_config(num_epochs=1, num_iterations=1)
      train_with_cleanup(trainer, output_dir)
      record = trainer.predict(
          "This is a text", as_argilla_records=True
      )
      assert isinstance(record, TextClassificationRecord)
      assert record.multi_label is False
      not_record = trainer.predict(
          "This is a text", as_argilla_records=False
      )
      assert not isinstance(not_record, TextClassificationRecord)
      train_with_cleanup(trainer, output_dir, train=False)
  
imports: from argilla.client.models import TextClassificationRecord
  from argilla.training import ArgillaTrainer
  from .helpers import train_with_cleanup
label_desc: Use image node_id 2 for calling a global function with example usage: test_setfit_train(dataset_text_classification) without return types