How to use Deehan1866/finetuned-sentence-transformers-multi-qa-mpnet-base-dot-v1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Deehan1866/finetuned-sentence-transformers-multi-qa-mpnet-base-dot-v1") sentences = [ "Google SEO expert Matt Cutts had a similar experience, of the eight magazines and newspapers Cutts tried to order, he received zero.", "He dissolved the services of her guards and her court attendants and seized an expansive reach of properties belonging to her.", "Google SEO expert Matt Cutts had a comparable occurrence, of the eight magazines and newspapers Cutts tried to order, he received zero.", "bill's newest solo play, \"all over the map\", premiered off broadway in april 2016, produced by all for an individual cinema." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
