Text Classification
Transformers
Safetensors
English
German
cybersecurity
prompt-injection
data-exfiltration
clef
custom-code
Eval Results (legacy)
Instructions to use TextCortex/clef-cybersecurity with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use TextCortex/clef-cybersecurity with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="TextCortex/clef-cybersecurity")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("TextCortex/clef-cybersecurity", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download assets/benchmark-auroc.png from TextCortex/clef-cybersecurity: direct link, hf CLI and curl.
- Browser
- Download file 148 kB
-
https://huggingface.co/TextCortex/clef-cybersecurity/resolve/main/assets/benchmark-auroc.png
- Command line
-
hf download hf://TextCortex/clef-cybersecurity/assets/benchmark-auroc.png
-
curl -L -o benchmark-auroc.png https://huggingface.co/TextCortex/clef-cybersecurity/resolve/main/assets/benchmark-auroc.png
148 kB

- Xet hash:
- 2bb537ee10e8e7ec770c236b69ea5367a4ecd5db920db47d82211896976c92b2
- Size of remote file:
- 148 kB
- SHA256:
- cb67d379a9905e1b56e184d11b31c5ff5e8bce1b4658a53e2ad38c1af6d5d8ac
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