sentence-transformers How to use KhaledReda/all-MiniLM-L6-v46-pair_score with sentence-transformers:
from sentence_transformers import SentenceTransformer
model = SentenceTransformer("KhaledReda/all-MiniLM-L6-v46-pair_score")
sentences = [
"ginger",
"13-inch - space grey 512 gb 13-inch color space grey size numeric 13 - inch spec 512 gb",
"steel pro power pro rectangular frame swimming pool ws water toy swimming pool water capacity swimming pool filter pump swimming pool pvc swimming pool unisex swimming pool boys swimming pool girls swimming pool polyester swimming pool power pro pool rectangular frame pool steel pro pool power pro pool rectangular frame pool steel pro pool sport swimming steel pro pool enjoy the heat of the summer by staying cool when you have the steel pro rectangular frame above ground swimming pool. it is easy to set up and thanks to the rust resistant steel frame and heavy duty pvc and polyester 3 ply sidewalls you know it will last for years to come. as easy as it is to set-up taking it down at the end of the season is just as easy making it a wonderful choice for you and you can rest easy knowing your lawn is not in danger. pool with metal structure measuring 300 cm long x 201 cm wide x 66 cm high. the frame model ensures a greater volume of water compared to similar surface fast set models. the surface pools are very easy to assembl",
"strips craft supply crafts strips a kilo of leaves stips."
]
embeddings = model.encode(sentences)
similarities = model.similarity(embeddings, embeddings)
print(similarities.shape)
# [4, 4] 
