from typing import List


def save_topics(model, vectorizer, top_n: int=10)-> List:
    """Save the top n topics from our trained model
    
    Args:
        model: Sklearn LatentDirichletAllocation model
        vectorizer: sklearn CountVectorizer
        top_n (int): Number of topics
    
    Returns:
        list: A list of the top_n words for each topic 
        
    """
    words_per_topic = []
    for idx, topic in enumerate(model.components_):
        words = [vectorizer.get_feature_names()[i] for i in topic.argsort()[:-top_n-1:-1]]
        words_per_topic.append(words)
        
    return words_per_topic