code: def get_preset_custom(name, problem_type):
      if not isinstance(name, str):
          raise ValueError(
              f"Expected string value for custom model, but was given {name}"
          )
      # Custom model
      if name == "GBMLarge":
          model = get_param_baseline_custom(problem_type)
          model[AG_ARGS] = dict(
              model_type="GBM",
              name_suffix="Large",
              hyperparameter_tune_kwargs=None,
              priority=0,
          )
          return [model]
      else:
          raise ValueError(f"Unknown custom model preset: {name}")
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_preset_custom(name, problem_type) and returns: list