How to use justOneMoreTestCase/insurance-rag-embeddings with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("justOneMoreTestCase/insurance-rag-embeddings", trust_remote_code=True) sentences = [ "How can I contact my LIC agent or nearest branch according to the provided instructions?", "Contact your LIC agent or nearest branch or\nvisit our website\nor\nwww.licindia.in\nSMS\nto\n, (e.g. Mumbai.’)\n‘YOUR CITY NAME’\n566773", "LIC's JEEVAN AROGYA (UIN: 512N266V02)\n(A Non-linked, Non-Parcipang,\nIndividual, Health Insurance Plan)\nLIC's Jeevan Arogya is a unique non-parcipang non-linked plan which provides\nhealth insurance cover against certain specified health risks and provides you with\nmely support in case of medical emergencies and helps you and your family remain\nfinanciallyindependentindifficultmes.\nHealth has been a major concern on everybody's mind, including yours. In these days\nofskyrockengmedicalexpenses,whenafamilymemberisill,itisatraumacmefor\nthe rest of the family. As a caring person, you do not want to let any unfortunate\nincident to affect your plans for you and your family. So why let any medical\nemergenciessha eryourpeaceofmind.", "Contact your LIC agent or nearest branch or\nvisit our website\nor\nwww.licindia.in\nSMS\nto\n, (e.g. Mumbai.’)\n‘YOUR CITY NAME’\n566773" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
