Instructions to use SkillScreen/SkillScreen-2B-Package-Experimental with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SkillScreen/SkillScreen-2B-Package-Experimental with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SkillScreen/SkillScreen-2B-Package-Experimental")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("SkillScreen/SkillScreen-2B-Package-Experimental") model = AutoModelForSequenceClassification.from_pretrained("SkillScreen/SkillScreen-2B-Package-Experimental", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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Download README.md from SkillScreen/SkillScreen-2B-Package-Experimental: direct link, hf CLI and curl.
- Browser
- Download file 1.5 kB
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https://huggingface.co/SkillScreen/SkillScreen-2B-Package-Experimental/resolve/main/README.md
- Command line
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hf download hf://SkillScreen/SkillScreen-2B-Package-Experimental/README.md
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curl -L -o README.md https://huggingface.co/SkillScreen/SkillScreen-2B-Package-Experimental/resolve/main/README.md
1.5 kB
metadata
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
- experimental
SkillScreen-2B-Package-Experimental
Experimental 2B decision model for SKILL.md and related file contents.
Trained on the recovered SRC010 package cohort with a 32K input budget.
Based on OpenJev 2B. Full weights are at the root.
The original LoRA adapter and classification head are in adapter/.
Use
Requires CUDA with BF16 support.
pip install huggingface_hub
hf download SkillScreen/SkillScreen-2B-Package-Experimental --revision v1 --local-dir skillscreen
pip install -r skillscreen/requirements.txt
python skillscreen/score.py path/to/package.json
Native maliciousness score ≥ 0.5 is flagged as suspicious.
package.json contains Markdown and companion file text.
{"skill_text": "Contents of SKILL.md", "files": [{"path": "scripts/helper.py", "text": "File contents"}]}
Checkpoint details · Export verification · Project page · Code
Jerrold Huang, Junwei Quan, Saiyue Lyu, Zihan Guo, Yingqiang Ge.