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howwhenRaw
/
llm-for-sec-secjev

Text Classification
jev-style
Safetensors
Chinese
English
qwen3
security
decision-model
safety-perception
lora
Model card Files Files and versions
xet
Community

Instructions to use howwhenRaw/llm-for-sec-secjev with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • jev-style

    How to use howwhenRaw/llm-for-sec-secjev with jev-style:

    pip install "jev-style[torch]"
    from jev_style import JevStyle, noul, choice
    
    js = JevStyle.from_pretrained("howwhenRaw/llm-for-sec-secjev")
    out = js.decide("I was charged twice for one order.", {
        "billing": noul("This message is about billing."),
        "team": choice("Which team should handle it?", ["billing", "shipping", "tech"]),
    })
    print(out["answers"]["team"]["choice"])
  • Notebooks
  • Google Colab
  • Kaggle
llm-for-sec-secjev
1.28 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 21 commits
howwhenRaw's picture
howwhenRaw
Upload adapter-r2/slots.json with huggingface_hub
1ff4987 verified 19 days ago
  • adapter-r1
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  • adapter-r2
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  • .gitattributes
    1.57 kB
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  • README.md
    4.1 kB
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  • chat_template.jinja
    4.2 kB
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  • config.json
    1.48 kB
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  • generation_config.json
    170 Bytes
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  • head.pt
    89.4 kB
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  • model.safetensors
    1.19 GB
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  • render_eval.py
    11 kB
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  • slots.json
    694 Bytes
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  • tokenizer.json
    11.4 MB
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  • tokenizer_config.json
    750 Bytes
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