How to use spl4shedEdu/mpnet_ESB with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("spl4shedEdu/mpnet_ESB") sentences = [ "mohawk industries mqrt01425 72 inch rustic suede hickory laminate quarter round mqrt01425 cork bamboo tile more stepco nuvelle high gloss flooring sale hardwood mohawk industries toolsandhomeimprovement", "nokya heavy duty headlight harnesses high beam 0305 toyota mrs mrs 9005hb3 or as complete upgrades a precautionary measure against harness plug burnouts which can permanently damage your toyota mrs headlight housings these heavy duty headlight high beam 9005 wire harnesses also help to handle the increased demands of aftermarket bulbs nokya offers these harnesses cheap and relatively easy upgrade stock electrical system they work replacements for damaged plugs lighting are not designed extended periods use operation in adverse severe conditions to address this brand otherwise each set consists 2 harnesses these have been be plugged into mrss wiring aftermarket automotive", "mohawk industries mqrt01425 72 inch rustic suede hickory laminate quarter round mqrt01425 cork bamboo tile mincp01425 barrington 846quot instaform profile sale hardwood mohawk industries toolsandhomeimprovement", "fuel hose 120 x 170 mm outside cloth braided 1994 bmw 318i base convertible fuel system page 1 note working pressure 7 bar sold by the meter cohline automotive" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
https://huggingface.co/spl4shedEdu/mpnet_ESB/resolve/main/tokenizer.json
hf download hf://spl4shedEdu/mpnet_ESB/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/spl4shedEdu/mpnet_ESB/resolve/main/tokenizer.json
