How to use jebish7/bge_MNSR with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jebish7/bge_MNSR") sentences = [ "Could you clarify the process for determining whether an entity is subject to FATCA and the ADGM Common Reporting Standard Regulations 2017?", "If Rule 7.5.3(b) or 7.5.3(c) applies, the Insurance Intermediary must, if requested by the Retail Client, provide to that Client a list of insurers with whom it deals or may deal in relation to the relevant Contracts of Insurance.", "REGULATORY REQUIREMENTS FOR AUTHORISED PERSONS ENGAGED IN REGULATED ACTIVITIES IN RELATION TO VIRTUAL ASSETS\nInternational Tax Reporting Obligations\nCOBS Rule 17.4 requires Authorised Persons to consider and, if applicable, adhere to their tax reporting obligations including, as applicable, under the Foreign Account Tax Compliance Act (“FATCA”) and the ADGM Common Reporting Standard Regulations 2017.\n", "The following lists some of the items that an Authorised Person should consider including in its internal reporting of Operational Risks:\na.\tthe results of monitoring activities;\nb.\tassessments of the Operational Risk framework performed by control functions such as internal audit, compliance, risk management and/or external audit;\nc.\treports generated by (and/or for) supervisory authorities;\nd.\tmaterial breaches of the Authorised Person's risk appetite and tolerance with respect to Operational Risk;\ne.\tdetails of recent significant internal Operational Risk events and losses, including near misses or events that resulted in a positive return; and\nf.\trelevant external events and any potential impact on the Authorised Person and its Operational Risk framework, including Operational Risk capital." ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
