code: def test_import_model_has_required_files():
      revision = "3956d303d3cddf0708ff20660c1ea5f6ec30e434"
      labels = {"framework": "transformers"}
      bento_model = bentoml.transformers.import_model(
          "tiny-bert",
          "hf-internal-testing/tiny-random-BertModel",
          sync_with_hub_version=True,
          revision=revision,
          labels=labels,
      )
  
      assert os.path.exists(bento_model.path_of("config.json"))
      assert os.path.exists(bento_model.path_of("pytorch_model.bin"))
      assert os.path.exists(bento_model.path_of("pretrained.v2.pkl"))
      assert os.path.exists(bento_model.path_of("model.yaml"))
      assert bento_model.info.labels == labels
      bentoml.models.delete(
          "tiny-bert:3956d303d3cddf0708ff20660c1ea5f6ec30e434"
      )
  
imports: from __future__ import annotations
  import logging
  import os
  import typing
  import pytest
  import transformers
  from transformers.models.auto.modeling_auto import AutoModelForAudioClassification
  from transformers.models.auto.modeling_auto import AutoModelForCausalLM
  from transformers.models.auto.modeling_auto import AutoModelForSequenceClassification
  from transformers.pipelines import check_task
  from transformers.pipelines import pipeline
  from transformers.pipelines.audio_classification import AudioClassificationPipeline
  from transformers.trainer_utils import set_seed
  import bentoml
  from bentoml.exceptions import BentoMLException
  from bentoml.transformers import ModelOptions
label_desc: Use image node_id 13 for calling a global function with example usage: test_import_model_has_required_files() without return types