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---
language:
- zh
pretty_name: OpenGuardrailsMixZh_97k
---
# OpenGuardrailsMixZh 97k
- **Repository:** [openguardrails/OpenGuardrailsMixZh_97k](https://huggingface.co/openguardrails/OpenGuardrailsMixZh_97k)
- **License:** Apache 2.0
- **Paper:** [OpenGuardrails: An Open-Source Context-Aware AI Guardrails Platform](https://arxiv.org/abs/2510.19169)
- **Code:** [openguardrails/openguardrails](https://github.com/openguardrails/openguardrails)
## 📘 Dataset Summary
**OpenGuardrailsMixZh 97k** is a large-scale **Chinese safety dataset collection** introduced in the [OpenGuardrails](https://arxiv.org/abs/2510.19169) paper.
It consists of **97,000 Chinese samples** curated, translated, and aligned from several well-known English safety datasets, designed for **multilingual safety evaluation** and **guardrail model training**.
This dataset provides a diverse coverage of safety-related scenarios such as:
* Toxic and unsafe language
* Jailbreak and prompt-injection attempts
* Ethical and legal compliance
* Sensitive topics and harmful instructions
## 📚 Source Composition
OpenGuardrailsMixZh combines translated and aligned subsets from the following datasets:
| Source Dataset | Description | License |
| -------------- | ------------------------------------------------------------------------- | ---------- |
| ToxicChat | Multi-turn dialogues containing toxicity and moderation-relevant language | CC BY 4.0 |
| WildGuardMix | Diverse unsafe prompts for red-teaming and alignment | Apache 2.0 |
| PolyGuard | Multi-lingual safety dataset for LLM guardrails | Apache 2.0 |
| XSTest | Cross-lingual safety test dataset | Apache 2.0 |
| BeaverTails | Large-scale red teaming dataset for safety and refusal behavior | Apache 2.0 |
All datasets were **machine-translated** to ensure high-quality Chinese representations.
## 📊 Dataset Statistics
| Attribute | Value |
| ---------------------- | ------------------------------------------------------------- |
| Total Samples | 97,000 |
| Languages | Chinese (Simplified) |
| Tasks | Safety classification, refusal prediction, toxicity detection |
| Avg. Tokens per sample | ~180 |
| Data Type | Instruction–Response pairs with safety annotations |
## 🧠 Intended Uses
* Fine-tuning and evaluating **Chinese guardrail models**
* Benchmarking multilingual **LLM safety performance**
* Research on **cross-lingual safety transfer** and **alignment robustness**
## Limitations
* Some translations may lose subtle cultural or contextual nuances.
* Safety labels were aligned from English datasets and may not fully capture **Chinese socio-cultural sensitivities**.
* The dataset is intended **for research purposes only**, not for deployment in production without additional validation.
## Citation
If you use this dataset, please cite the following paper:
```bibtex
@misc{openguardrails,
title={OpenGuardrails: An Open-Source Context-Aware AI Guardrails Platform},
author={Thomas Wang and Haowen Li},
year={2025},
url={https://arxiv.org/abs/2510.19169},
}
```
## License
This dataset is released under the **Apache 2.0 License**.
Please refer to the original source datasets for their respective licenses when using subsets.
## Acknowledgements
We thank the creators of **ToxicChat**, **WildGuardMix**, **PolyGuard**, **XSTest**, and **BeaverTails** for making their datasets publicly available, enabling cross-lingual safety research.