code: def model_markdown(self):
      long_name = AlgorithmsRegistry.get_long_name(
          self._ml_task, self.learner_params["model_type"]
      )
      short_name = self.learner_params["model_type"]
      desc = f"# Summary of {self.get_name()}\n\n"
  
      desc += "[<< Go back](../README.md)\n\n"
  
      if long_name == short_name:
          desc += f"\n## {short_name}\n"
      else:
          desc += f"\n## {long_name} ({short_name})\n"
      for k, v in self.learner_params.items():
          if k in ["model_type", "ml_task", "seed"]:
              continue
          desc += f"- **{k}**: {v}\n"
      desc += "\n## Validation\n"
      for k, v in self.validation_params.items():
          if "path" not in k:
              desc += f" - **{k}**: {v}\n"
      desc += "\n## Optimized metric\n"
      desc += f"{self.get_metric_name()}\n"
      desc += "\n## Training time\n"
      desc += f"\n{np.round(self.train_time,1)} seconds\n"
      return desc
  
imports: import copy
  import gc
  import json
  import logging
  import os
  import sys
  import time
  import uuid
  import zipfile
  import numpy
  import pandas
  from supervised.algorithms.factory import AlgorithmFactory
  from supervised.algorithms.registry import BINARY_CLASSIFICATION, MULTICLASS_CLASSIFICATION, REGRESSION, AlgorithmsRegistry
  from supervised.callbacks.callback_list import CallbackList
  from supervised.exceptions import AutoMLException
  from supervised.preprocessing.exclude_missing_target import ExcludeRowsMissingTarget
  from supervised.preprocessing.preprocessing import Preprocessing
  from supervised.utils.additional_metrics import AdditionalMetrics
  from supervised.utils.config import LOG_LEVEL
  from supervised.utils.metric import Metric
  from supervised.validation.validation_step import ValidationStep
  from supervised.utils.jsonencoder import MLJSONEncoder
  import joblib
  import optuna
  from supervised.tuner.optuna.tuner import OptunaTuner
  from supervised.utils.config import mem
  from supervised.utils.learning_curves import LearningCurves
label_desc: Use image node_id 24 for calling the ModelFramework obj's underlying member method code with example usage: obj.model_markdown() and returns: desc