How to use much1na/ettin-encoder-17m-denseon-embeddistill with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("much1na/ettin-encoder-17m-denseon-embeddistill") sentences = [ "which president is credited with inspiring the maxwell house slogan' good to the last drop", "what two important benefits do heterotrophs derive from photosynthesis?", "what is the nauru solution", "1 An estimate of the total cost of a new passport for your child/children can be obtained using the Estimate Your Costs calculator. 2 According to Family Vacation Critic, a website that features reviews of family-friendly hotels, resorts, destinations and attractions, the application fee for children below 16 is $80. The passports are valid for 5 years until the age of 16, at which time a new passport will be required. 2 The requirements needed when applying for a minor passport are as follows: evidence of citizenship, photo identification, parental consent, passport photo, application forms, and passport fees." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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