code: def test_small_model_tf(self):
      text_classifier = pipeline(
          task="text-classification",
          model="hf-internal-testing/tiny-random-distilbert",
          framework="tf",
      )
  
      outputs = text_classifier("This is great !")
      self.assertEqual(
          nested_simplify(outputs),
          [{"label": "LABEL_0", "score": 0.504}],
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/pipelines/test_pipelines_text_classification.py
imports: import unittest
  from transformers import MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, TextClassificationPipeline, pipeline
  from transformers.testing_utils import nested_simplify, require_tf, require_torch, slow
  from .test_pipelines_common import ANY, PipelineTestCaseMeta
label_desc: Use image node_id 3 for calling the TextClassificationPipelineTests obj's underlying member method code with example usage: obj.test_small_model_tf() without return types