input: def classify_string(input_string):
      """
      Creates a machine learning classifier in Python for categorizing user input.
      The classifier uses the Multinomial Naive Bayes algorithm.
      >>> classify_string("Hello")
      ['Greetings']
      >>> classify_string("Goodbye")
      ['Farewell']
      """
output:     
      from sklearn.feature_extraction.text import CountVectorizer
      from sklearn.naive_bayes import MultinomialNB
      from sklearn.pipeline import make_pipeline
  
      # Sample training data
      data = ["Hello", "Hi", "Hey", "Goodbye", "Bye", "Farewell"]
      labels = ["Greetings", "Greetings", "Greetings", "Farewell", "Farewell", "Farewell"]
  
      # Create a pipeline with CountVectorizer and MultinomialNB
      model = make_pipeline(CountVectorizer(), MultinomialNB())
      model.fit(data, labels)
  
      # Predict the category of the input string
      return model.predict([input_string])
  