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 NOTICE from TextCortex/clef-cybersecurity: direct link, hf CLI and curl.
- Browser
- Download file 422 Bytes
-
https://huggingface.co/TextCortex/clef-cybersecurity/resolve/main/NOTICE
- Command line
-
hf download hf://TextCortex/clef-cybersecurity/NOTICE
-
curl -L -o NOTICE https://huggingface.co/TextCortex/clef-cybersecurity/resolve/main/NOTICE
422 Bytes
| clef-cybersecurity | |
| Fine-tuning, benchmark assembly and inference integration by TextCortex. | |
| Based on Cloudflare/clef-flash, revision 17f0b0ad64efb65d273590632833508766b2aae6, | |
| and its Qwen/Qwen3.5-9B backbone, released under Apache-2.0. | |
| The inference integration is an exported subset of the benchmarked implementation. | |
| Upstream joint_schema_model.py is downloaded from that pinned revision and hash-checked before import. | |