What is SBERT?

SBERT (Sentence-BERT) is a modification of the BERT network that uses Siamese and triplet network structures to derive semantically meaningful sentence embeddings that can then be compared using cosine similarity. It is commonly used for tasks like semantic textual similarity, clustering, and information retrieval because it significantly reduces the computational effort of comparing sentences compared to traditional BERT applications.