How to use Jrinky/model4 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Jrinky/model4") sentences = [ "What do studies show about the configurations of eukaryotic polysomes", "Eukaryotic\n\nIn cells \nin situ (in cell) studies have shown that eukaryotic polysomes exhibit linear configurations. Densely packed 3-D helices and planar double-row polysomes were found with variable packing including “top-to-top” contacts similar to prokaryotic polysomes.", "Carlo Dante Rota (born 17 April 1961) is a British-born Canadian actor. He has appeared in Little Mosque on the Prairie and as systems analyst Morris O'Brian on the Fox series 24.", "Ronnie & Jo Wood Still ‘Close Friends’ Despite Joint Property Auction\nCelebrity auctioneer Darren Julien is gearing up for a massive sale of over 600 items belonging to Rolling Stones guitarist Ronnie Wood’s and his ex-wife Jo Wood. Much like many of Julian’s Auctions past collections, this auction has created some controversy because Ronnie has recently come out as opposed to the sale of his personal belongings, denying his involvement in the ‘joint’ sale. In response to those recent statements coming out Ronnie Wood’s camp saying he’s “shocked and disappointed” at the auctioning off his personal belongings, and that the auction has been “misrepresented as a joint sale,” Julien claims Ronnie has known about the auction since its start." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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