File size: 1,441 Bytes
ad9806e | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 | ---
library_name: transformers
pipeline_tag: text-classification
license: other
license_name: skillscreen-proprietary
license_link: LICENSE
base_model: AlexWortega/openjev
datasets:
- ProtectSkills/MaliciousSkillBench
tags:
- skillscreen
- agent-security
- nli
- sd
---
# SkillScreen-2B-SD
This model is described in the paper: [SkillScreen: High-Recall Screening of Malicious Agent Skills with Decision Models](https://huggingface.co/papers/2610.17727).
2B decision model for detecting malicious agent skills from `SKILL.md`. Trained on MaliciousSkillBench using Source-Disjoint (SD), with an 8K input budget.
Based on [OpenJev 2B](https://huggingface.co/AlexWortega/openjev). Full weights are at the root. The original LoRA adapter and classification head are in `adapter/`.
## Use
Requires CUDA with BF16 support.
```bash
pip install huggingface_hub
hf download SkillScreen/SkillScreen-2B-SD --revision v1 --local-dir skillscreen
pip install -r skillscreen/requirements.txt
python skillscreen/score.py path/to/SKILL.md
```
Native maliciousness score **≥ 0.5** is flagged as suspicious.
[Checkpoint details](provenance.json) · [Export verification](merge_verification.json) · [Project page](https://jerroldh.github.io/SkillScreen-webpage/) · [Code](https://github.com/JerroldH/SkillScreen)
Jerrold Huang, Junwei Quan, Saiyue Lyu, Zihan Guo, Yingqiang Ge.
[License](LICENSE) · [Third-party notices](THIRD_PARTY_NOTICES.md)
|