How to use yinong333/finetuned_MiniLM with sentence-transformers:
from sentence_transformers import SentenceTransformer model = SentenceTransformer("yinong333/finetuned_MiniLM") sentences = [ "Why is it important to establish clear timelines for data retention, and what should happen to data once those timelines are reached?", "Technology \nDignari \nDouglas Goddard \nEdgar Dworsky \nElectronic Frontier Foundation \nElectronic Privacy Information \nCenter, Center for Digital \nDemocracy, and Consumer \nFederation of America \nFaceTec \nFight for the Future \nGanesh Mani \nGeorgia Tech Research Institute \nGoogle \nHealth Information Technology \nResearch and Development \nInteragency Working Group \nHireVue \nHR Policy Association \nID.me \nIdentity and Data Sciences \nLaboratory at Science Applications \nInternational Corporation \nInformation Technology and \nInnovation Foundation \nInformation Technology Industry \nCouncil \nInnocence Project \nInstitute for Human-Centered \nArtificial Intelligence at Stanford \nUniversity \nIntegrated Justice Information \nSystems Institute \nInternational Association of Chiefs \nof Police \nInternational Biometrics + Identity \nAssociation \nInternational Business Machines \nCorporation \nInternational Committee of the Red \nCross \nInventionphysics \niProov \nJacob Boudreau \nJennifer K. Wagner, Dan Berger,", "new privacy risks and implementing appropriate mitigation measures, which may include express consent. \nClear timelines for data retention should be established, with data deleted as soon as possible in accordance \nwith legal or policy-based limitations. Determined data retention timelines should be documented and justi\nfied. \nRisk identification and mitigation. Entities that collect, use, share, or store sensitive data should \nattempt to proactively identify harms and seek to manage them so as to avoid, mitigate, and respond appropri\nately to identified risks. Appropriate responses include determining not to process data when the privacy risks \noutweigh the benefits or implementing measures to mitigate acceptable risks. Appropriate responses do not \ninclude sharing or transferring the privacy risks to users via notice or consent requests where users could not \nreasonably be expected to understand the risks without further support.", "55. Data & Trust Alliance. Algorithmic Bias Safeguards for Workforce: Overview. Jan. 2022. https://\ndataandtrustalliance.org/Algorithmic_Bias_Safeguards_for_Workforce_Overview.pdf\n56. Section 508.gov. IT Accessibility Laws and Policies. Access Board. https://www.section508.gov/\nmanage/laws-and-policies/\n67" ] embeddings = model.encode(sentences) similarities = model.similarity(embeddings, embeddings) print(similarities.shape) # [4, 4]
https://huggingface.co/yinong333/finetuned_MiniLM/resolve/main/tokenizer.json
hf download hf://yinong333/finetuned_MiniLM/tokenizer.json
curl -L -o tokenizer.json https://huggingface.co/yinong333/finetuned_MiniLM/resolve/main/tokenizer.json
