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yinong333
/
finetuned_MiniLM

Sentence Similarity
sentence-transformers
Safetensors
bert
feature-extraction
Generated from Trainer
dataset_size:760
loss:MatryoshkaLoss
loss:MultipleNegativesRankingLoss
Eval Results (legacy)
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use yinong333/finetuned_MiniLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    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]
  • Notebooks
  • Google Colab
  • Kaggle
finetuned_MiniLM
91.8 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
yinong333's picture
yinong333
Add new SentenceTransformer model.
000786b verified over 1 year ago
  • 1_Pooling
    Add new SentenceTransformer model. over 1 year ago
  • .gitattributes
    1.52 kB
    initial commit over 1 year ago
  • README.md
    37 kB
    Add new SentenceTransformer model. over 1 year ago
  • config.json
    656 Bytes
    Add new SentenceTransformer model. over 1 year ago
  • config_sentence_transformers.json
    201 Bytes
    Add new SentenceTransformer model. over 1 year ago
  • model.safetensors
    90.9 MB
    xet
    Add new SentenceTransformer model. over 1 year ago
  • modules.json
    349 Bytes
    Add new SentenceTransformer model. over 1 year ago
  • sentence_bert_config.json
    53 Bytes
    Add new SentenceTransformer model. over 1 year ago
  • special_tokens_map.json
    695 Bytes
    Add new SentenceTransformer model. over 1 year ago
  • tokenizer.json
    712 kB
    Add new SentenceTransformer model. over 1 year ago
  • tokenizer_config.json
    1.43 kB
    Add new SentenceTransformer model. over 1 year ago
  • vocab.txt
    232 kB
    Add new SentenceTransformer model. over 1 year ago