How to use KhaledReda/all-MiniLM-L6-v64-pair_score with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KhaledReda/all-MiniLM-L6-v64-pair_score") sentences = [ "trichup thermal protection", "eocene serucene hr serum f/all hr 100m eocene serucene", "zilly bar chair adds an elegant and stylistic flair to home or office interior. a luxurious touch to your home . dimensions 75 cm seat height 42 cm width 42 cm depth . material base metal back fabric.", "oranges green navel - 2.5 kg per pack green oranges navel oranges" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
