Model overview
**Llama-3.1-Nemotron-Safety-Guard-8B-v3** is a multilingual content safety model that moderates human-LLM interaction content and classifies user prompts and LLM responses as safe or unsafe. If the content is unsafe, the model additionally returns a response with a list of categories that the content violates. It supports 9 languages: English, Spanish, Mandarin, German, French, Hindi, Japanese, Arabic, and Thai. The base large language model (LLM) is the multilingual Llama-3.1-8B-Instruct model from Meta. NVIDIA’s optimized release is LoRa-tuned on approved datasets and better conforms to NVIDIA’s content safety risk taxonomy and other safety risks in human-LLM interactions. The model is trained using the Nemotron-Safety-Guard-Dataset-v3 dataset which is synthetically curated using the CultureGuard pipeline. The model shows strong zero-shot generalization supporting over 20 languages (en, ar, de, es, fr, hi, ja, th, zh, it, ko, nl, cs, da, fi, iw, pt-BR, pl, ru, sv). The model can be prompted using an instruction and a taxonomy of unsafe risks to be categorized. The instruction format for prompt moderation is shown below under input and output examples. For a detailed description of the dataset and model, please see our paper . Experience the model in the NVIDIA NIM Preview here.
Key features
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Limitations & considerations
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Source prices & cost analysis
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Estimate monthly base token costs
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Public benchmarks & run configuration
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Sources & traceability
许可证：other。模型介绍与第三方评测均以原来源的具体版本和方法为准。