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AtliQ-Technologies/guardex-distilbert-safety

sourceHugging Faceupdated 3mo agoView on Hugging Face

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Model Card

GuardEx DistilBERT Safety Classifier

Binary classifier that labels a piece of text as safe or unsafe. Used by GuardEx, an LLM guardrail library, as one of its content-safety models. This is the fastest of the GuardEx classifiers, with the lowest accuracy of the three.

Labels

id	label
0	safe
1	unsafe

Performance

Held-out evaluation:

—F1: 0.720

Usage

python

from transformers import AutoTokenizer, AutoModelForSequenceClassification
import torch

repo = "AtliQ-Technologies/guardex-distilbert-safety"
tok = AutoTokenizer.from_pretrained(repo)
model = AutoModelForSequenceClassification.from_pretrained(repo)

enc = tok("text to check", return_tensors="pt", truncation=True, max_length=128)
with torch.no_grad():
    logits = model(**enc).logits
print(model.config.id2label[int(logits.argmax())])  # "safe" or "unsafe"

Details

Fine-tuned from martin-ha/toxic-comment-model. Max sequence length 128.