input: Write a function display_digit_recognizer_code() that generates and displays the Python code for a Machine Learning model capable of recognizing handwritten digits from 0 to 9. The function should print the code directly without returning anything.
  assert display_digit_recognizer_code() is None
output: def display_digit_recognizer_code():
      code = '''
  from sklearn import datasets
  from sklearn.model_selection import train_test_split
  from sklearn.preprocessing import StandardScaler
  from sklearn.neighbors import KNeighborsClassifier
  from sklearn.metrics import accuracy_score
  
  # Load dataset
  digits = datasets.load_digits()
  
  # Split data into training and testing sets
  X_train, X_test, y_train, y_test = train_test_split(digits.data, digits.target, test_size=0.2, random_state=42)
  
  # Standardize the features
  scaler = StandardScaler()
  X_train = scaler.fit_transform(X_train)
  X_test = scaler.transform(X_test)
  
  # Initialize and train the KNN classifier
  knn = KNeighborsClassifier(n_neighbors=3)
  knn.fit(X_train, y_train)
  
  # Predict and evaluate the model
  y_pred = knn.predict(X_test)
  accuracy = accuracy_score(y_test, y_pred)
  print(f"Model Accuracy: {accuracy:.2f}")
  '''
      print(code)