How to use jebish7/snowflake_1 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("jebish7/snowflake_1", trust_remote_code=True) sentences = [ "According to the Client Money Auditor's Report, how did the Authorised Person manage Client Money—was it pooled in a single client Account or segregated into individual Client Accounts as per COBS Chapter 14?", "The written notice in Rule 6.2.1(a)(i) must make it explicit that, if an Employee is prohibited from undertaking a Personal Account Transaction, he must not, except in the proper course of his employment:\n(a)\tprocure another Person to enter into such a Transaction; or\n(b)\tcommunicate any information or opinion to another Person if he knows, or ought to know, that the Person will as a result, enter into such a Transaction or procure some other Person to do so.", "Client Money Auditor's Report:An Authorised Person must, in procuring the production of a Client Money Auditor's Report, ensure that an Auditor states, as at the date of which the Authorised Person's audited statement of financial position was prepared:\n(1)\tthe amount of Client Money an Authorised Person was holding and controlling in accordance with COBS Chapter 14; and\n(2)\twhether:\n(a)\tthe Authorised Person has maintained throughout the year systems and controls to enable it to comply with the relevant provisions of COBS Chapter 14;\n(b)\tthe Authorised Person's controls are such as to ensure that Client Money is identifiable and secure at all times;\n(c)\tany of the requirements in COBS Chapter 14 have not been met;\n(d)\tClient Money has been pooled in a single client Account or segregated in Client Accounts maintained for individual Clients in accordance with COBS Chapter 14;\n(e)\tif applicable, the Authorised Person as holding and controlling the appropriate amount of Client Money in accordance with COBS Chapter 14 as at the date on which the Authorised Person's audited statement of financial position was prepared;\n(f)\tthe Auditor has received all necessary information and explanations for the purposes of preparing the report to the Regulator; and\n(g)\tif applicable, there have been any material discrepancies in the reconciliation of Client Money.", "CRS Options\n/Table Start\nNo.\tOPTIONS\tCOMMENTS\n1.\tAlternative approach to calculating account balances\tNO\n2.\tUse of other reporting period\tNO\n3.\tFiling deadlines\t30th June\n4.\tFiling Nil returns\tYES\n5.\tAllowing third party service providers to fulfil the obligations on behalf of\nthe Financial Institutions\tYES\n6.\tAllowing the due diligence procedures for New Accounts to be used for\nPre-existing Accounts\tYES\n7.\tAllowing the due diligence procedures for High Value Accounts to be used\nfor Lower Value Accounts\tYES\n8.\tResidence address test for Lower Value Accounts\tYES\n9.\tExclusion from Due Diligence for Pre-existing Entity Accounts not exceeding $250,000\tYES\n10.\tAlternative documentation procedure for certain employer-sponsored\ngroup insurance contracts or annuity contracts\tYES\n11.\tAllowing Financial Institutions to make greater use of existing\nstandardised industry coding systems for the due diligence process\tYES\n12.\tCurrency translation\tUSE USD$\n\n13.\tAllow a Financial Institution to treat certain New Accounts held by pre-existing customers as a Pre-existing Account for due diligence purposes\tYES\n14.\tExpanded definition of Related Entity for Investment Entities\tYES\n15.\tGrandfathering rule for bearer shares issued by Exempt Collective\nInvestment Vehicle\tRemoved\n16.\tPhasing in the requirements to report gross proceeds\tNO\n/Table End\n\n" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
