input: Write a function to create a pipeline for text classification using CountVectorizer and SVC from sklearn.
  assert isinstance(create_text_pipeline(), Pipeline)
  assert 'vectorizer' in create_text_pipeline().named_steps
  assert 'classifier' in create_text_pipeline().named_steps
output: def create_text_pipeline():
      from sklearn.pipeline import Pipeline
      from sklearn.feature_extraction.text import CountVectorizer
      from sklearn.svm import SVC
      
      pipeline = Pipeline([
          ('vectorizer', CountVectorizer()),
          ('classifier', SVC())
      ])
      return pipeline