input: def create_digit_classifier(dataset_name: str) -> LogisticRegression:
      """Generate a machine learning model in Python using scikit-learn for classifying digits in the specified dataset.
      >>> created_model = create_digit_classifier('mnist_784')
      >>> prediction = created_model.predict([X[0]])
      >>> y[0] == prediction[0]
      True
      """
  
output:     from sklearn.datasets import fetch_openml
      from sklearn.model_selection import train_test_split
      from sklearn.linear_model import LogisticRegression
      from sklearn.preprocessing import StandardScaler
      from sklearn.pipeline import make_pipeline
  
      data = fetch_openml(name=dataset_name, version=1, as_frame=False)
      X, y = data.data, data.target
      X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
  
      model = make_pipeline(StandardScaler(), LogisticRegression(max_iter=200))
      model.fit(X_train, y_train)
  
      return model