code: def test_dump_timm_image():
      download_dir = "./"
      model_dump_path = "./timm_image_test"
      base_model_name = "mobilenetv3_large_100"
      train_data, _ = shopee_dataset(download_dir=download_dir)
      predictor_1 = MultiModalPredictor(
          label="label",
      )
      hyperparameters = {
          "optimization.max_epochs": 1,
          "model.names": ["timm_image_1"],
          "model.timm_image_1.checkpoint_name": base_model_name,
      }
      predictor_1.fit(
          train_data=train_data,
          hyperparameters=hyperparameters,
          time_limit=5,
          seed=42,
      )
      predictor_1.dump_model(save_path=model_dump_path)
      model = timm.create_model(
          model_name=base_model_name,
          checkpoint_path=f"{model_dump_path}/timm_image_1/pytorch_model.bin",
          num_classes=0,
      )
      assert isinstance(model, timm.models.mobilenetv3.MobileNetV3)
      predictor_2 = MultiModalPredictor(
          label="label",
      )
      hyperparameters = {
          "optimization.max_epochs": 1,
          "model.timm_image.checkpoint_name": f"{model_dump_path}/timm_image_1",
      }
      predictor_2.fit(
          train_data=train_data,
          hyperparameters=hyperparameters,
          time_limit=5,
          seed=42,
      )
  
file_path: autogluon/multimodal/tests/unittests/others/test_dump_model.py
imports: import os
  import pytest
  import timm
  import transformers
  from autogluon.core.utils.loaders import load_zip
  from autogluon.multimodal import MultiModalPredictor
  from autogluon.multimodal.utils.misc import shopee_dataset
  from ..utils.unittest_datasets import AEDataset, PetFinderDataset
label_desc: Use image node_id 1 for calling a global function with example usage: test_dump_timm_image() without return types