How to use Muhammad2003/router-embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("Muhammad2003/router-embedding") sentences = [ "In a complex legal scenario involving multiple jurisdictions, how would you navigate the differences in laws related to online privacy violations and harassment?", "How does voluntary admission under the Baker Act impact eligibility for a Concealed Weapon Permit?", "How do the terms of the account and the circumstances impact the potential liability of the Bank of Hawaii in this situation?", "Can someone run a background check on you without your consent?" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
