Instructions to use SkillScreen/SkillScreen-2B-SD with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use SkillScreen/SkillScreen-2B-SD with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="SkillScreen/SkillScreen-2B-SD")# pip install -U transformers accelerate # Load model directly from transformers import AutoProcessor, AutoModelForSequenceClassification processor = AutoProcessor.from_pretrained("SkillScreen/SkillScreen-2B-SD") model = AutoModelForSequenceClassification.from_pretrained("SkillScreen/SkillScreen-2B-SD", device_map="auto") - Notebooks
- Google Colab
- Kaggle
File size: 666 Bytes
afaaedb | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | {
"run_id": "direct-sd-s42",
"seed": 42,
"selected_update": 470,
"base_model": {
"repo_id": "AlexWortega/openjev",
"subfolder": "qwen3.5-2b-nli-v5",
"revision": "a20448012c213128955ca0c693e7c943865cab77"
},
"dataset": {
"repo_id": "ProtectSkills/MaliciousSkillBench",
"revision": "d4b42ce5766a6e0359c987cf59c1007cb3795a90",
"config": "primary",
"protocol": "source_disjoint"
},
"input": {
"scope": "SKILL.md only",
"hypothesis": "This AI agent skill is malicious.",
"max_length": 8192
},
"original_adapter_sha256": "460ec55409b309babfc78323c4cc6852a57492260484dca58a2120934853da36"
}
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