sentence-transformers How to use KhaledReda/all-MiniLM-L6-v63-pair_score with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("KhaledReda/all-MiniLM-L6-v63-pair_score")
sentences = [
"copad s",
"waffle potato bites cheese sauce waffle potatoes yogurt waffle potatoes beef bacon waffle potatoes appetizers patat bites waffle patat bites slices of waffle potatoes served with cheese sauce and mint yogurt with the addition of beef bacon bites sweet relish and pickles.",
"zpac - reusable shopping bag - green color ecofriendly shopping bag plastic shopping bag green shopping bag zpac - reusable shopping bag - nan reusable shopping bags are durable and eco-friendly alternatives to single-use plastic bags. made from recycled fabric these bags are designed to withstand multiple uses and carry heavy loads. they feature sturdy handles and spacious interiors providing ample space for groceries clothing and other items.",
"educational laptop for multicolor laptop toy plastic laptop toy develop auditory skills toy laptop toy this fun is designed in the form of a children s laptop with a cute cartoon face of a fun animal. it provides a variety of musical activities and cheerful lights that stimulate the child s interaction and encourage him to explore. teach your child shapes colors and numbers through large easy-to-use colorful buttons. in addition to familiar educational songs that help enhance children s auditory and cognitive skills. it s a safe toy suitable for ages 3 and up making it the perfect companion for fun and learning. features stimulate early learning the child learned shapes and numbers in a fun and easy way. develop auditory and musical skills through famili"
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
