code: def test_small_model_tf(self):
      zero_shot_classifier = pipeline(
          "zero-shot-classification",
          model="sshleifer/tiny-distilbert-base-cased-distilled-squad",
          framework="tf",
      )
      outputs = zero_shot_classifier(
          "Who are you voting for in 2020?",
          candidate_labels=["politics", "public health", "science"],
      )
  
      self.assertEqual(
          nested_simplify(outputs),
          {
              "sequence": "Who are you voting for in 2020?",
              "labels": ["science", "public health", "politics"],
              "scores": [0.333, 0.333, 0.333],
          },
      )
  
file_path: H2O/h2o_flexgen/benchmark/third_party/transformers/tests/pipelines/test_pipelines_zero_shot.py
imports: import unittest
  from transformers import MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING, Pipeline, ZeroShotClassificationPipeline, 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 ZeroShotClassificationPipelineTests obj's underlying member method code with example usage: obj.test_small_model_tf() without return types