from sklearn.feature_extraction.text import TfidfVectorizer  

# Your documents  
documents = [  
    "The cat sat on the mat",  
    "The cat sat on the hat",  
    "The dog lay on the mat"  
]  

# Create and fit the vectorizer  
vectorizer = TfidfVectorizer()  
tfidf_matrix = vectorizer.fit_transform(documents)  

# See the vocabulary  
print(vectorizer.get_feature_names_out())  
# ['cat', 'dog', 'hat', 'lay', 'mat', 'on', 'sat', 'the']  

# See the TF-IDF scores for document 1  
print(tfidf_matrix[0].toarray())