How to use knguyennguyen/mpnet_20k with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("knguyennguyen/mpnet_20k") sentences = [ "I'm in search of a durable cover that can safeguard my cycling device while still allowing easy access to its features. It should be lightweight and available in different color options.", "Title: Portable Radio AM FM KAVNLON-001 Descripion: ['1']", "Title: GE WB27T11078 Keypanel Supt Asm Wh Descripion: ['This is an O.E.M. Authorized part . This is an authorized aftermarket product. Fits with various WB27T11078 brand models.']", "Title: Garmin 010-12791-00 Silicone Case, Edge 530, Black Descripion: ['Protect your Edge® 830 with this form-fitting, removable silicone case. Available in other colors (sold separately).']" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
