input: def classify_mnist_digits(dataset: str) -> object:
      """ Generate a machine learning model using scikit-learn for classifying digits in the specified dataset.
      >>> classify_mnist_digits('mnist_784')
      (array([...], dtype=float32), array([...], dtype=float32))
      """
      from sklearn.datasets import fetch_openml
      import numpy as np
      from sklearn.linear_model import LogisticRegression
      
      mnist = fetch_openml(dataset)
      X = mnist.data
      y = mnist.target
      X = X.reshape((X.shape[0], -1))
      clf = LogisticRegression()
      clf.fit(X, y)
      return X, y
output:     X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=42)
      clf.fit(X_train, y_train)
      y_pred = clf.predict(X_test)
      accuracy = np.mean(y_pred == y_test)
      print(f"Model accuracy: {accuracy:.2f}")
      return X_train, y_train