code: def load_trained_model(f: str = ""):
      """
      load a saved model from file
      @param f: path to model
      @return: loaded model
      """
      try:
          if not f:
              logger.info(
                  f"result path: {configs.get('results_path')} "
              )
              logger.info(
                  f"loading model form {configs.get('default_model_path')} "
              )
              with open(
                  configs.get("default_model_path"), "rb"
              ) as _model:
                  model = joblib.load(_model)
          else:
              logger.info(f"loading from {f}")
              with open(f, "rb") as _model:
                  model = joblib.load(_model)
          return model
      except FileNotFoundError:
          logger.error(
              f"File not found in {configs.get('default_model_path')}"
          )
  
file_path: igel/igel/utils.py
imports: import json
  import logging
  import joblib
  import pandas
  import yaml
  from igel.configs import configs
  from igel.data import metrics_dict, models_dict
label_desc: Use image node_id 6 for calling a global function with example usage: load_trained_model(f) and returns: model