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1from sentence_transformers import CrossEncoder
2model = CrossEncoder('efederici/cross-encoder-umberto-stsb')
3scores = model.predict([('Sentence 1', 'Sentence 2'), ('Sentence 3', 'Sentence 4')])('Sentence 1', 'Sentence 2') and ('Sentence 3', 'Sentence 4').