How to use BelisaDi/stella-tuned-rirag with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("BelisaDi/stella-tuned-rirag", trust_remote_code=True) sentences = [ "When calculating regulatory capital, which guidance note outlines the potential for an increased valuation adjustment for less liquid positions that may surpass the adjustments made for financial reporting purposes?", "REGULATORY REQUIREMENTS - SPOT COMMODITY ACTIVITIES\nSpot Commodities and Accepted Spot Commodities\nAuthorised Persons will need to submit the details of how each Accepted Spot Commodity that is proposed to be used meets the requirements for the purposes of COBS Rule 22.2.2 and paragraphs 25 and 26 above. The use of each Accepted Spot Commodity will be approved as part of the formal application process for review and approval of an FSP. Though an Authorised Person may, for example, propose to admit to trading a commonly traded Spot Commodity, the Authorised Person’s controls relating to responsible and sustainable sourcing, and sound delivery mechanisms may not yet be fully developed. In such circumstances, the FSRA may require the Authorised Person to delay the commencement of trading until such time that suitable controls have been developed and implemented.\n", "Adjustment to the current valuation of less liquid positions for regulatory capital purposes. The adjustment to the current valuation of less liquid positions made under Guidance note 11 is likely to impact minimum Capital Requirements and may exceed those valuation adjustments made under the International Financial Reporting Standards and Guidance notes 8 and 9.\n\n", "REGULATORY REQUIREMENTS FOR AUTHORISED PERSONS ENGAGED IN REGULATED ACTIVITIES IN RELATION TO VIRTUAL ASSETS\nAnti-Money Laundering and Countering Financing of Terrorism\nIn order to develop a robust and sustainable regulatory framework for Virtual Assets, FSRA is of the view that a comprehensive application of its AML/CFT framework should be in place, including full compliance with, among other things, the:\n\na)\tUAE AML/CFT Federal Laws, including the UAE Cabinet Resolution No. (10) of 2019 Concerning the Executive Regulation of the Federal Law No. 20 of 2018 concerning Anti-Money Laundering and Combating Terrorism Financing;\n\nb)\tUAE Cabinet Resolution 20 of 2019 concerning the procedures of dealing with those listed under the UN sanctions list and UAE/local terrorist lists issued by the Cabinet, including the FSRA AML and Sanctions Rules and Guidance (“AML Rules”) or such other AML rules as may be applicable in ADGM from time to time; and\n\nc)\tadoption of international best practices (including the FATF Recommendations).\n" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
