code: def test_inference_model(self):
      tokenizer = FunnelTokenizer.from_pretrained(
          "huggingface/funnel-small"
      )
      model = FunnelModel.from_pretrained("huggingface/funnel-small")
      inputs = tokenizer(
          "Hello! I am the Funnel Transformer model.",
          return_tensors="pt",
      )
      output = model(**inputs)[0]
  
      expected_output_sum = torch.tensor(235.7246)
      expected_output_mean = torch.tensor(0.0256)
      self.assertTrue(
          torch.allclose(output.sum(), expected_output_sum, atol=1e-4)
      )
      self.assertTrue(
          torch.allclose(output.mean(), expected_output_mean, atol=1e-4)
      )
  
imports: import unittest
  from transformers import FunnelConfig, FunnelTokenizer, is_torch_available
  from transformers.models.auto import get_values
  from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device
  from ...test_configuration_common import ConfigTester
  from ...test_modeling_common import ModelTesterMixin, ids_tensor
label_desc: Use image node_id 2 for calling the FunnelModelIntegrationTest obj's underlying member method code with example usage: obj.test_inference_model() without return types