code: def test_small_model_tf(self):
      model_name = (
          "hf-internal-testing/tiny-bert-for-token-classification"
      )
      token_classifier = pipeline(
          task="token-classification", model=model_name, framework="tf"
      )
      outputs = token_classifier("This is a test !")
      self.assertEqual(
          nested_simplify(outputs),
          [
              {
                  "entity": "I-MISC",
                  "score": 0.115,
                  "index": 1,
                  "word": "this",
                  "start": 0,
                  "end": 4,
              },
              {
                  "entity": "I-MISC",
                  "score": 0.115,
                  "index": 2,
                  "word": "is",
                  "start": 5,
                  "end": 7,
              },
          ],
      )
  
imports: import unittest
  import numpy
  from transformers import MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING, TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING, AutoModelForTokenClassification, AutoTokenizer, TokenClassificationPipeline, pipeline
  from transformers.pipelines import AggregationStrategy, TokenClassificationArgumentHandler
  from transformers.testing_utils import is_pipeline_test, nested_simplify, require_tf, require_torch, require_torch_accelerator, slow, torch_device
  from .test_pipelines_common import ANY
label_desc: Use image node_id 17 for calling the TokenClassificationPipelineTests obj's underlying member method code with example usage: obj.test_small_model_tf() without return types