code: def test_tf_bert(self):
      text_classifier = pipeline("text-classification", framework="tf")
  
      outputs = text_classifier("This is great !")
      self.assertEqual(
          nested_simplify(outputs),
          [{"label": "POSITIVE", "score": 1.0}],
      )
      outputs = text_classifier("This is bad !")
      self.assertEqual(
          nested_simplify(outputs),
          [{"label": "NEGATIVE", "score": 1.0}],
      )
      outputs = text_classifier("Birds are a type of animal")
      self.assertEqual(
          nested_simplify(outputs),
          [{"label": "POSITIVE", "score": 0.988}],
      )
  
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 5 for calling the TextClassificationPipelineTests obj's underlying member method code with example usage: obj.test_tf_bert() without return types