text: Title: [BUG] TimeSeriesPredictor.load very slow on first run
  Body: **Bug Report Checklist**
  <!-- Please ensure at least one of the following to help the developers troubleshoot the problem:  -->
  - [x] I provided code that demonstrates a minimal reproducible example. <!-- Ideal, especially via source install --> 
  - [x] I confirmed bug exists on the latest mainline of AutoGluon via source install. <!-- Preferred --> 
  - [ ] I confirmed bug exists on the latest stable version of AutoGluon. <!-- Unnecessary if prior items are checked --> 
  
  **Describe the bug**
  <!-- A clear and concise description of what the bug is. -->
  When you load a pre-trained model for the first time, the it takes a very long time to load, almost as long as if you were training it all over again.  This makes it almost unusable in time sensitive environments.  This does not happen on subsequent runs.
  
  **Expected behavior**
  <!-- A clear and concise description of what you expected to happen. -->
  When you run TimeSeriesPredictor.load(path=model_path) first time, it is very slow.  On each subsequent run, it is very fast.
  Someone mentioned in another thread that it appeared temporary directories were being created the first time a model is loaded and this might be the cause.  I have not confirmed this.
  
  **To Reproduce**
  <!-- A minimal script to reproduce the issue. Links to Colab notebooks or similar tools are encouraged.  
  If the code is too long, feel free to put it in a public gist and link it in the issue: https://gist.github.com.  
  In short, we are going to copy-paste your code to run it and we expect to get the same result as you. -->
  try:
          # Format the model path
          formatted_date = pd.to_datetime(model_date).strftime("%Y%m%d")
          model_path = os.path.join('models', f"{set_name}_{months_history}m_{formatted_date}")
          
          logger.info(f"Loading predictor from: {model_path}")
          
          if not os.path.exists(model_path):
              raise FileNotFoundError(f"No predictor found at: {model_path}")
              
          predictor = TimeSeriesPredictor.load(path=model_path)
          logger.info(f"Successfully loaded predictor for {set_name}")
          return predictor
          
      except Exception as e:
          logger.error(f"Error loading predictor: {str(e)}")
          raise
  
  **Screenshots / Logs**
  <!-- If applicable, add screenshots or logs to help explain your problem. -->
  
  **Installed Versions**
  <!-- Please run the following code snippet: -->
  <details>
  
  INSTALLED VERSIONS
  ------------------
  date                   : 2024-10-30
  time                   : 18:17:54.872890
  python                 : 3.10.12.final.0
  OS                     : Linux
  OS-release             : 5.4.0-196-generic
  Version                : #216-Ubuntu SMP Thu Aug 29 13:26:53 UTC 2024
  machine                : x86_64
  processor              : x86_64
  num_cores              : 48
  cpu_ram_mb             : 192039.9921875
  cuda version           : 12.535.183.01
  num_gpus               : 1
  gpu_ram_mb             : [14923]
  avail_disk_size_mb     : 202650
  
  accelerate             : 0.21.0
  autogluon              : 1.1.1
  autogluon.common       : 1.1.1
  autogluon.core         : 1.1.1
  autogluon.features     : 1.1.1
  autogluon.multimodal   : 1.1.1
  autogluon.tabular      : 1.1.1
  autogluon.timeseries   : 1.1.1
  boto3                  : 1.35.38
  catboost               : 1.2.7
  defusedxml             : 0.7.1
  evaluate               : 0.4.3
  fastai                 : 2.7.17
  gluonts                : 0.15.1
  hyperopt               : 0.2.7
  imodels                : None
  jinja2                 : 3.1.4
  joblib                 : 1.4.2
  jsonschema             : 4.21.1
  lightgbm               : 4.3.0
  lightning              : 2.3.3
  matplotlib             : 3.9.2
  mlforecast             : 0.10.0
  networkx               : 3.4
  nlpaug                 : 1.1.11
  nltk                   : 3.9.1
  nptyping               : 2.4.1
  numpy                  : 1.26.4
  nvidia-ml-py3          : 7.352.0
  omegaconf              : 2.2.3
  onnxruntime-gpu        : None
  openmim                : 0.3.9
  optimum                : 1.17.1
  optimum-intel          : None
  orjson                 : 3.10.7
  pandas                 : 2.2.3
  pdf2image              : 1.17.0
  Pillow                 : 10.4.0
  psutil                 : 5.9.8
  pytesseract            : 0.3.10
  pytorch-lightning      : 2.3.3
  pytorch-metric-learning: 2.3.0
  ray                    : 2.10.0
  requests               : 2.32.3
  scikit-image           : 0.20.0
  scikit-learn           : 1.4.0
  scikit-learn-intelex   : None
  scipy                  : 1.12.0
  seqeval                : 1.2.2
  setuptools             : 65.5.0
  skl2onnx               : None
  statsforecast          : 1.4.0
  tabpfn                 : None
  tensorboard            : 2.17.1
  text-unidecode         : 1.3
  timm                   : 0.9.16
  torch                  : 2.3.1
  torchmetrics           : 1.2.1
  torchvision            : 0.18.1
  tqdm                   : 4.66.5
  transformers           : 4.40.2
  utilsforecast          : 0.0.10
  vowpalwabbit           : None
  xgboost                : 2.0.3
  
  ```python
  # Replace this code with the output of the following:
  from autogluon.core.utils import show_versions
  show_versions()
  ```
  
  </details>
  