code: def test_embed_untrained(self):
      classification_kwargs = {
          "use_differentiable_head": self.use_differentiable_head
      }
      setfit_model_args = SetFitModelArguments(
          "sentence-transformers/paraphrase-MiniLM-L3-v2"
      )
      clf_factory = SetFitClassificationFactory(
          setfit_model_args,
          self.num_classes,
          classification_kwargs=classification_kwargs,
      )
  
      train_set = twenty_news_text(
          20, num_classes=self.num_classes, multi_label=self.multi_label
      )
  
      clf = clf_factory.new()
      with self.assertRaisesRegex(ValueError, "Model is not trained"):
          clf.embed(train_set)
  
imports: import unittest
  import pytest
  import numpy
  from unittest.mock import patch
  from scipy.sparse import issparse
  from small_text.data.datasets import TextDataset
  from small_text.exceptions import UnsupportedOperationException
  from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
  from sklearn.utils.validation import check_is_fitted
  from tests.utils.datasets import twenty_news_text
label_desc: Use image node_id 1 for calling the _EmbeddingTest obj's underlying member method code with example usage: obj.test_embed_untrained() without return types