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selfconstruct3d
/
AttackGroup-MPNET

Feature Extraction
Transformers
Safetensors
English
mpnet
cybersecurity
classification
fine-tuned
text-embeddings-inference
Model card Files Files and versions
xet
Community

Instructions to use selfconstruct3d/AttackGroup-MPNET with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use selfconstruct3d/AttackGroup-MPNET with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("feature-extraction", model="selfconstruct3d/AttackGroup-MPNET")
    # Load model directly
    from transformers import AutoTokenizer, AutoModel
    
    tokenizer = AutoTokenizer.from_pretrained("selfconstruct3d/AttackGroup-MPNET")
    model = AutoModel.from_pretrained("selfconstruct3d/AttackGroup-MPNET")
  • Notebooks
  • Google Colab
  • Kaggle
AttackGroup-MPNET
440 MB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 19 commits
selfconstruct3d's picture
selfconstruct3d
Update README.md
944949c verified 6 months ago
  • .gitattributes
    1.52 kB
    initial commit about 1 year ago
  • README.md
    11.3 kB
    Update README.md 6 months ago
  • added_tokens.json
    4.98 kB
    Upload tokenizer about 1 year ago
  • config.json
    607 Bytes
    Upload model about 1 year ago
  • label_to_groupid.json
    2.19 kB
    Upload label_to_groupid.json with huggingface_hub about 1 year ago
  • model.safetensors
    439 MB
    xet
    Upload model about 1 year ago
  • special_tokens_map.json
    964 Bytes
    Upload tokenizer about 1 year ago
  • tokenizer.json
    752 kB
    Upload tokenizer about 1 year ago
  • tokenizer_config.json
    40.1 kB
    Upload tokenizer about 1 year ago
  • vocab.txt
    232 kB
    Upload tokenizer about 1 year ago