natolambert/xstest-v2-copy
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How to use Crusadersk/quantsafe-refusal-modernbert with Transformers:
# Use a pipeline as a high-level helper
from transformers import pipeline
pipe = pipeline("text-classification", model="Crusadersk/quantsafe-refusal-modernbert") # Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification
tokenizer = AutoTokenizer.from_pretrained("Crusadersk/quantsafe-refusal-modernbert")
model = AutoModelForSequenceClassification.from_pretrained("Crusadersk/quantsafe-refusal-modernbert")A compact binary classifier used by QuantSafe Certifier to distinguish semantic
refusals from compliant responses. Label 1 is refusal; label 0 is
compliance.
answerdotai/ModernBERT-base pinned to 8949b909ec900327062f0ebf497f51aef5e6f0c820260613| Method | Accuracy | Macro F1 | Refusal F1 |
|---|---|---|---|
| This model | 0.9773 | 0.9773 | 0.9760 |
| QuantSafe legacy opener lexicon | 0.5261 | 0.4124 | 0.1538 |
The model is a refusal detector, not a general-purpose harmfulness classifier. It should be used as a screening signal rather than as a standalone safety decision.
Base model
answerdotai/ModernBERT-base