code: def test_log_load_model(caplog: pytest.LogCaptureFixture):
      with caplog.at_level(logging.DEBUG):
          bento_model = bentoml.transformers.save_model(
              "sentiment_test",
              pipeline(
                  task="text-classification",
                  model="hf-internal-testing/tiny-random-distilbert",
              ),
          )
          _ = bentoml.transformers.load_model(
              "sentiment_test:latest", use_fast=True
          )
      assert (
          f"Loading '{t.cast(ModelOptions, bento_model.info.options).task!s}' pipeline (tag='{bento_model.tag!s}')"
          in caplog.text
      )
  
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 8 for calling a global function with example usage: test_log_load_model(caplog) without return types