input: 
  def identify_author(samples: List[str], labels: List[str]) -> Pipeline:
      """Develop a machine learning model in Python to identify the author of a given article.
      
      >>> identify_author(["sample 1 from AuthorA", "sample 2 from AuthorA", "sample 1 from AuthorB", "sample 2 from AuthorB"], ["AuthorA", "AuthorA", "AuthorB", "AuthorB"])
      Pipeline(steps=[('tfidf', TfidfVectorizer()), ('clf', GaussianNB())])
      """
  
output:     from sklearn.feature_extraction.text import TfidfVectorizer
      from sklearn.naive_bayes import GaussianNB
      from sklearn.pipeline import Pipeline
  
      tfidf = TfidfVectorizer()
      clf = GaussianNB()
  
      pipeline = Pipeline(steps=[('tfidf', tfidf), ('clf', clf)])
  
      return pipeline