How to use KhaledReda/all-MiniLM-L6-v44-pair_score with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("KhaledReda/all-MiniLM-L6-v44-pair_score") sentences = [ "aquafresh toothpaste", "slogan grey t-shirt, grey tshirt cotton tshirt oversized tshirt kids tshirt boys tshirt slogan tshirt tshirt jersi slogan jersi slogan t shirt t shirt, slogan tshirt tshirt jersi slogan jersi slogan t shirt t shirt, gender boys age 12-18 months petite generic t-shirt slogan types of fashion styles casual fit oversized cotton grey, product details 100 cotton oversized fit.", "eva smokers mouthwash menthol 250 ml, eva eva mouthwash eva smokers menthol mouthwash mouthwash, units 250 millilitre", "toplo blanket with sleeves foot pocket, winter blanket winter wearable blanket unisex wearable blanket women wearable blanket men wearable blanket foot pocket blanket sleeves blanket toplo blanket wearable blanket, foot pocket blanket sleeves blanket toplo blanket wearable blanket, gender unisex women men magalis generic blanket toplo one pocket style foot pocket sleeve style long fit loose rose pink season winter fashion style sleeve, our wearable blanket is the best choice to keep you warm and cozy on those cold winter nights from head to toe while lounging on sofa / bed watching tv napping reading a book or studying." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
