code: def test_load_model_options():
      model: transformers.PreTrainedModel = (
          transformers.AutoModelForCausalLM.from_pretrained("gpt2")
      )
      tokenizer: transformers.PreTrainedTokenizer = (
          transformers.AutoTokenizer.from_pretrained("gpt2")
      )
  
      bentoml.transformers.save_model(
          "gpt2", model, custom_objects={"tokenizer": tokenizer}
      )
  
      bentomodel = bentoml.models.get("gpt2")
      _model = bentomodel.load_model()
      assert isinstance(_model, transformers.PreTrainedModel)
      _tokenizer = bentomodel.custom_objects["tokenizer"]
      assert isinstance(
          _tokenizer, transformers.PreTrainedTokenizerBase
      )
  
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 1 for calling a global function with example usage: test_load_model_options() without return types