code: def test_init_model_loading_strategy_always_local(self):
      model_loading_strategy = ModelLoadingStrategy.ALWAYS_LOCAL
      setfit_model_args = SetFitModelArguments(
          "sentence-transformers/all-MiniLM-L6-v2",
          model_loading_strategy=model_loading_strategy,
      )
      num_classes = 5
  
      if not self.use_differentiable_head:
          model_kwargs = {"multi_target_strategy": "one-vs-rest"}
      else:
          model_kwargs = {}
  
      with patch(
          "setfit.modeling.SetFitModel.from_pretrained"
      ) as from_pretrained_mock:
          SetFitClassification(
              setfit_model_args,
              num_classes,
              multi_label=self.multi_label,
              model_kwargs=model_kwargs,
              use_differentiable_head=self.use_differentiable_head,
          )
          self.assertEqual(1, from_pretrained_mock.call_count)
          self.assertFalse(
              from_pretrained_mock.call_args.kwargs["force_download"]
          )
          self.assertTrue(
              from_pretrained_mock.call_args.kwargs["local_files_only"]
          )
  
imports: import unittest
  import pytest
  from unittest.mock import patch
  from small_text.integrations.pytorch.exceptions import PytorchNotFoundError
label_desc: Use image node_id 5 for calling the _SetFitClassification obj's underlying member method code with example usage: obj.test_init_model_loading_strategy_always_local() without return types