PolyGuard Qwen Smol EU AI Act Compliance Profile

PolyGuard: A Multilingual Safety Moderation Tool for 17 Languages

Abstract: Truly multilingual safety moderation efforts for Large Language Models (LLMs) have been hindered by a narrow focus on a small set of languages (e.g., English, Chinese) as well as a limited scope of safety definition, resulting in significant gaps in moderation capabilities. To bridge these gaps, we release PolyGuard, a new state-of-the-art multilingual safety model for safeguarding LLM generations, and the corresponding training and evaluation datasets. PolyGuard is trained on PolyGuardMix, the largest multilingual safety training corpus to date containing 1.91M samples across 17 languages (e.g., Chinese, Czech, English, Hindi). We also introduce PolyGuardPrompts, a high quality multilingual benchmark with 29K samples for the evaluation of safety guardrails. Created by combining naturally occurring multilingual human-LLM interactions and human-verified machine translations of an English-only safety dataset (WildGuardMix; Han et al., 2024), our datasets contain prompt-output pairs with labels of prompt harmfulness, response harmfulness, and response refusal. Through extensive evaluations across multiple safety and toxicity benchmarks, we demonstrate that PolyGuard outperforms existing state-of-the-art open-weight and commercial safety classifiers by 5.5%. Our contributions advance efforts toward safer multilingual LLMs for all global users.

How to Use PolyGuard

from transformers import AutoTokenizer, AutoModelForCausalLM
import torch

model_id = "ToxicityPrompts/PolyGuard-Qwen-Smol"
tokenizer = AutoTokenizer.from_pretrained(model_id)
model = AutoModelForCausalLM.from_pretrained(model_id)

SYSTEM_PROMPT = """You are a classifier for analyzing interactions between humans and LLMs. Given a request from a human user and a response from an LLM assistant, determine 1) whether the human user's request is harmful, 2) whether the AI assistant's response is a refusal, and 3) whethe

Your obligations as a PolyGuard Qwen Smol deployer

Track your progress

Sign up to track obligations, receive deadline reminders, and generate audit packages.

Tags

Languages