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willchen0011
/
SecEBL

Sentence Similarity
sentence-transformers
Joblib
Safetensors
modernbert
security
intrusion-detection
behavior-analytics
intent-recognition
linux
kubernetes
audit-log
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use willchen0011/SecEBL with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • sentence-transformers

    How to use willchen0011/SecEBL with sentence-transformers:

    from sentence_transformers import SentenceTransformer
    
    model = SentenceTransformer("willchen0011/SecEBL")
    
    sentences = [
        "That is a happy person",
        "That is a happy dog",
        "That is a very happy person",
        "Today is a sunny day"
    ]
    embeddings = model.encode(sentences)
    
    similarities = model.similarity(embeddings, embeddings)
    print(similarities.shape)
    # [4, 4]
  • Notebooks
  • Google Colab
  • Kaggle
SecEBL / examples /linux
9.31 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 2 commits
willchen0011's picture
willchen0011
Move Rev20 RFC to model root
697129c about 11 hours ago
  • example_gold.rev20.jsonl
    7.43 MB
    xet
    Move Rev20 RFC to model root about 11 hours ago
  • example_sessions.jsonl
    1.88 MB
    xet
    Add public benchmark subset to model card about 11 hours ago