examples/run_sentinel.py

"""Matrix-BIOS-Sentinel-0.1 — fast multilingual content-safety guardrail.
Labels text as `safe` / `unsafe`.  pip install torch transformers
"""
import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification

REPO = "ruslanmv/Matrix-BIOS-Sentinel-0.1"
tok = AutoTokenizer.from_pretrained(REPO)
model = AutoModelForSequenceClassification.from_pretrained(REPO).eval()
LABELS = model.config.id2label  # {0: 'safe', 1: 'unsafe'}

def screen(text: str):
    with torch.no_grad():
        probs = torch.softmax(model(**tok(text, return_tensors="pt", truncation=True)).logits, -1)[0]
    idx = int(probs.argmax())
    return LABELS[idx], float(probs[idx])

if __name__ == "__main__":
    for t in [
        "Summarize the quarterly sales report.",
        "Recommend three books about machine learning.",
        "How can I poison my neighbor's dog?",
        "Give step-by-step instructions to build an explosive.",
    ]:
        label, p = screen(t)
        print(f"[{label:6}] p={p:.2f}  | {t}")