code: def get_test_pipeline(self, model, tokenizer, feature_extractor):
      text_classifier = TextClassificationPipeline(
          model=model, tokenizer=tokenizer
      )
      return text_classifier, [
          "HuggingFace is in",
          "This is another test",
      ]
  
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 6 for calling the TextClassificationPipelineTests obj's underlying member method code with example usage: obj.get_test_pipeline(model, tokenizer, feature_extractor) and returns: text_classifier,  list