How to use surajvbangera/mediclaim_embedding with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("surajvbangera/mediclaim_embedding") sentences = [ "Does my insurance policy exclude medical costs for the first 30 days' illness, but cover accident-related claims?", "any notice for renewal. \nb. Renewal shall not be denied on the ground that the insured person had made a claim or claims in the preceding \npolicy years.", "• Minimum entry age for proposer/ spouse/ dependent parents - 18 years\n• Maximum Entry Age for proposer/ spouse/ dependent parents - 80 years\n• Minimum Entry age for dependent Children - 3 months\n• Maximum Entry Age for dependent Children - 25 years", "a. Expenses related to the treatment of any illness within 30 days from the first policy commencement date shall \nbe excluded except claims arising due to an accident, provided the same are covered." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
