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MBuechel
/
TTP_SOK

Text Classification
Transformers
Safetensors
English
CTI
TTP
TTP Extraction
MITRE
ATT&CK
Model card Files Files and versions
xet
Community

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

  • Libraries
  • Transformers

    How to use MBuechel/TTP_SOK with Transformers:

    # Use a pipeline as a high-level helper
    from transformers import pipeline
    
    pipe = pipeline("text-classification", model="MBuechel/TTP_SOK")
    # Load model directly
    from transformers import AutoModel
    model = AutoModel.from_pretrained("MBuechel/TTP_SOK", dtype="auto")
  • Notebooks
  • Google Colab
  • Kaggle
TTP_SOK / Classification /data_augmentation /400_tram_artificial_FacebookAI-roberta-large
1.43 GB
Ctrl+K
Ctrl+K
  • 1 contributor
History: 1 commit
MBuechel's picture
MBuechel
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0eb8bc6 verified 11 months ago
  • classification_reports.txt
    59.7 kB
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  • config.json
    2.76 kB
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  • loss.pdf
    15 kB
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  • merges.txt
    456 kB
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  • model.safetensors
    1.42 GB
    xet
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  • model_params.json
    139 Bytes
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  • special_tokens_map.json
    280 Bytes
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  • stats.json
    5.62 kB
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  • tokenizer.json
    3.56 MB
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  • tokenizer_config.json
    1.22 kB
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  • vocab.json
    798 kB
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