How to use lw2134/policy_gte_large_7 with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("lw2134/policy_gte_large_7", trust_remote_code=True) sentences = [ "What are the expectations for automated systems in relation to data privacy?", "https://beta.nsf.gov/funding/opportunities/designing-accountable-software-systems-dass\n28. The Leadership Conference Education Fund. The Use Of Pretrial “Risk Assessment” Instruments: A\nShared Statement Of Civil Rights Concerns. Jul. 30, 2018. http://civilrightsdocs.info/pdf/criminal-justice/\nPretrial-Risk-Assessment-Short.pdf; https://civilrights.org/edfund/pretrial-risk-assessments/", "DATA PRIVACY \nWHAT SHOULD BE EXPECTED OF AUTOMATED SYSTEMS\nThe expectations for automated systems are meant to serve as a blueprint for the development of additional \ntechnical standards and practices that are tailored for particular sectors and contexts. \nIn addition to the privacy expectations above for general non-sensitive data, any system collecting, using, shar-", "standing that it may be these users who are most likely to need the human assistance. Similarly, it should be \ntested to ensure that users with disabilities are able to find and use human consideration and fallback and also \nrequest reasonable accommodations or modifications. \nConvenient. Mechanisms for human consideration and fallback should not be unreasonably burdensome as \ncompared to the automated system’s equivalent. \n49" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
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