How to use KhaledReda/all-MiniLM-L6-v36-pair_score with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KhaledReda/all-MiniLM-L6-v36-pair_score") sentences = [ "wide leg pants", "carefree d.inti.wash gre.tea a.vera 200 m category pharmacies women s care feminine hygiene feminine hygiene tags carefree carefree feminine wash daily intimate wash feminine wash intimate wash keywords carefree carefree feminine wash daily intimate wash feminine wash intimate wash attrs units 200 m", "blue star category fashion jewelry necklace necklace tags blue star necklaces women necklaces sterling silver 925 necklaces sterling silver necklaces silver necklaces necklaces star necklaces keywords necklaces star necklaces attrs gender women brand holley jewelry generic name necklaces product name blue star size free size types of fashion styles everyday wear casual material sterling silver 925 silver color blue description sterling silver 925.", "porland navy blue dinner plate - 27 cm category home and garden tableware plate and bowl dinner plate tags navy blue plate blue plate dinnerware dinner plate plate porland porland plate keywords dinner plate plate porland porland plate attrs color navy blue description discover the deepest shade of blue with porland s fine and minimal navy blue series. po-nb 18 cp 27" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
