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s2w-ai
/
CyBERTuned-SecurityLLM

Fill-Mask
Transformers
PyTorch
roberta
cybersecurity
Model card Files Files and versions
xet
Community
1

Instructions to use s2w-ai/CyBERTuned-SecurityLLM with libraries, inference providers, notebooks, and local apps. Follow these links to get started.

  • Libraries
  • Transformers

    How to use s2w-ai/CyBERTuned-SecurityLLM with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("fill-mask", model="s2w-ai/CyBERTuned-SecurityLLM")
    # Load model directly
    from transformers import AutoTokenizer, RobertaForTokClassAndMaskedLM
    
    tokenizer = AutoTokenizer.from_pretrained("s2w-ai/CyBERTuned-SecurityLLM")
    model = RobertaForTokClassAndMaskedLM.from_pretrained("s2w-ai/CyBERTuned-SecurityLLM")
  • Notebooks
  • Google Colab
  • Kaggle
CyBERTuned-SecurityLLM
502 MB
Ctrl+K
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  • 1 contributor
History: 3 commits
genesith's picture
genesith
Update README.md
cf1b7a4 verified almost 2 years ago
  • .gitattributes
    1.52 kB
    initial commit almost 2 years ago
  • README.md
    4.04 kB
    Update README.md almost 2 years ago
  • config.json
    1.03 kB
    Initial Commit almost 2 years ago
  • merges.txt
    456 kB
    Initial Commit almost 2 years ago
  • pytorch_model.bin

    Detected Pickle imports (4)

    • "torch.FloatStorage",
    • "torch._utils._rebuild_tensor_v2",
    • "collections.OrderedDict",
    • "torch.LongStorage"

    What is a pickle import?

    499 MB
    xet
    Initial Commit almost 2 years ago
  • special_tokens_map.json
    280 Bytes
    Initial Commit almost 2 years ago
  • tokenizer.json
    2.11 MB
    Initial Commit almost 2 years ago
  • tokenizer_config.json
    346 Bytes
    Initial Commit almost 2 years ago
  • vocab.json
    798 kB
    Initial Commit almost 2 years ago