code: def get_example_model(model):
      """
      Fetches the specified model from bnlearn repository and returns a
      pgmpy.model instance.
  
      Parameter
      ---------
      model: str
          Any model from bnlearn repository (http://www.bnlearn.com/bnrepository).
  
          Discrete Bayesian Network Options:
              Small Networks:
                  1. asia
                  2. cancer
                  3. earthquake
                  4. sachs
                  5. survey
              Medium Networks:
                  1. alarm
                  2. barley
                  3. child
                  4. insurance
                  5. mildew
                  6. water
              Large Networks:
                  1. hailfinder
                  2. hepar2
                  3. win95pts
              Very Large Networks:
                  1. andes
                  2. diabetes
                  3. link
                  4. munin1
                  5. munin2
                  6. munin3
                  7. munin4
                  8. pathfinder
                  9. pigs
                  10. munin
          Gaussian Bayesian Network Options:
                  1. ecoli70
                  2. magic-niab
                  3. magic-irri
                  4. arth150
          Conditional Linear Gaussian Bayesian Network Options:
                  1. sangiovese
                  2. mehra
  
      Example
      -------
      >>> from pgmpy.data import get_example_model
      >>> model = get_example_model(model='asia')
      >>> model
  
      Returns
      -------
      pgmpy.models instance: An instance of one of the model classes in pgmpy.models
                             depending on the type of dataset.
      """
      from pgmpy.readwrite import BIFReader
  
      filenames = {
          "asia": "utils/example_models/asia.bif.gz",
          "cancer": "utils/example_models/cancer.bif.gz",
          "earthquake": "utils/example_models/earthquake.bif.gz",
          "sachs": "utils/example_models/sachs.bif.gz",
          "survey": "utils/example_models/survey.bif.gz",
          "alarm": "utils/example_models/alarm.bif.gz",
          "barley": "utils/example_models/barley.bif.gz",
          "child": "utils/example_models/child.bif.gz",
          "insurance": "utils/example_models/insurance.bif.gz",
          "mildew": "utils/example_models/mildew.bif.gz",
          "water": "utils/example_models/water.bif.gz",
          "hailfinder": "utils/example_models/hailfinder.bif.gz",
          "hepar2": "utils/example_models/hepar2.bif.gz",
          "win95pts": "utils/example_models/win95pts.bif.gz",
          "andes": "utils/example_models/andes.bif.gz",
          "diabetes": "utils/example_models/diabetes.bif.gz",
          "link": "utils/example_models/link.bif.gz",
          "munin1": "utils/example_models/munin1.bif.gz",
          "munin2": "utils/example_models/munin2.bif.gz",
          "munin3": "utils/example_models/munin3.bif.gz",
          "munin4": "utils/example_models/munin4.bif.gz",
          "pathfinder": "utils/example_models/pathfinder.bif.gz",
          "pigs": "utils/example_models/pigs.bif.gz",
          "munin": "utils/example_models/munin.bif.gz",
          "ecoli70": "",
          "magic-niab": "",
          "magic-irri": "",
          "arth150": "",
          "sangiovese": "",
          "mehra": "",
      }
  
      if model not in filenames.keys():
          raise ValueError("dataset should be one of the options")
      if filenames[model] == "":
          raise NotImplementedError(
              "The specified dataset isn't available."
          )
  
      path = filenames[model]
      ref = files("pgmpy") / path
      with gzip.open(ref) as f:
          content = f.read()
      reader = BIFReader(string=content.decode("utf-8"), n_jobs=1)
      return reader.get_model()
  
label_desc: Use image node_id 1 for calling a global function with example usage: get_example_model(model) and returns: reader