Работал ли с задачами суммаризации

from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import cosine_similarity

def extractive_summary(text, n_sentences=3):
    sentences = text.split('. ')
    vectorizer = TfidfVectorizer().fit_transform(sentences)
    similarity_matrix = cosine_similarity(vectorizer)
    scores = similarity_matrix.sum(axis=1)
    top_indices = scores.argsort()[-n_sentences:][::-1]
    return '. '.join([sentences[i] for i in top_indices])

from transformers import pipeline
summarizer = pipeline("summarization", model="facebook/bart-large-cnn")  
summary = summarizer(text, max_length=130, min_length=30, do_sample=False)