text: import os
  from autogluon.text import TextPredictor
  from datasets import AmazonReviewSentimentCrossLingualDataset
  from test_automm_predictor import verify_predictor_save_load
  from utils import (
      download,
      protected_zip_extraction,
      get_home_dir,
  )
  
  
  def test_load_old_checkpoint():
      dataset = AmazonReviewSentimentCrossLingualDataset()
      sha1sum_id = "4ba096cdf6bd76c06386f2c27140db055e59c91b"
      checkpoint_name = "mdeberta-v3-base-checkpoint"
      save_path = os.path.join(get_home_dir(), "checkpoints")
      file_path = os.path.join(save_path, f"{checkpoint_name}.zip")
      checkpoint_path = os.path.join(get_home_dir(), "checkpoints", checkpoint_name)
      download(
          url=f"s3://automl-mm-bench/unit-tests-0.4/checkpoints/{checkpoint_name}.zip",
          path=file_path,
          sha1_hash=sha1sum_id,
      )
      protected_zip_extraction(
          file_path,
          sha1_hash=sha1sum_id,
          folder=save_path,
      )
      predictor = TextPredictor.load(checkpoint_path)
      verify_predictor_save_load(predictor, dataset.test_df)
  
      # continuous training
      predictor.fit(
          dataset.train_df,
          presets='multilingual',
          time_limit=10,
          hyperparameters={'optimization.top_k_average_method': 'uniform_soup'}
      )
      verify_predictor_save_load(predictor, dataset.test_df)
  