input: 
  def classify_mnist():
      """Loads the MNIST dataset and trains a Logistic Regression model to classify the digits.
      >>> classify_mnist()
      """
      # Import the necessary libraries 
      from sklearn.datasets import fetch_openml
      import numpy as np
      from sklearn.linear_model import LogisticRegression
  
      # Load the dataset
      mnist = fetch_openml('mnist_784')
  
      # Split into features and labels
      X = mnist.data
      y = mnist.target
  
      # Create a Logistic Regression classifier 
      clf = LogisticRegression()
  
      # Fit the model to the data 
      clf.fit(X, y)
  
      return clf
  
output:     
      # Predict on the training data
      y_pred = clf.predict(X)
  
      # Print the accuracy of the model
      accuracy = np.mean(y_pred == y)
      print(f"Accuracy: {accuracy:.2f}")
  