fastino
/

GLiNER2-Guardrails-PII-Multi

Token Classification

information-extraction

span-extraction

text-classification

multi-label-classification

jailbreak-detection

toxicity-classification

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 **`fastino/GLiNER2-Guardrails-PII-Multi`** is a single [GLiNER2](https://github.com/fastino-ai/GLiNER2) model that combines two capabilities in one checkpoint:
-1. **LLM safety moderation**: schema-conditioned guardrails for prompt/response safety, toxicity, jailbreak detection, and refusal classification (from [GLiGuard](https://huggingface.co/fastino/gliguard-LLMGuardrails-300M)).
 2. **PII detection & masking**: multilingual span-level extraction across 42 entity types (from [GLiNER2-PII](https://huggingface.co/fastino/gliner2-privacy-filter-PII-multi)).
 It is a fine-tune of GLiNER2 trained jointly on the **GLiGuard** and **fastino/gliner2-privacy-filter-PII-multi** datasets. The model is **multilingual** and its performance is **on par with the individual GLiGuard and GLiNER2-PII models** on their respective tasks, letting you replace two models with one.

 **`fastino/GLiNER2-Guardrails-PII-Multi`** is a single [GLiNER2](https://github.com/fastino-ai/GLiNER2) model that combines two capabilities in one checkpoint:
+1. **LLM guardrails & safety moderation**: schema-conditioned guardrails for prompt/response safety, toxicity, jailbreak detection, and refusal classification (from [GLiGuard](https://huggingface.co/fastino/gliguard-LLMGuardrails-300M)).
 2. **PII detection & masking**: multilingual span-level extraction across 42 entity types (from [GLiNER2-PII](https://huggingface.co/fastino/gliner2-privacy-filter-PII-multi)).
 It is a fine-tune of GLiNER2 trained jointly on the **GLiGuard** and **fastino/gliner2-privacy-filter-PII-multi** datasets. The model is **multilingual** and its performance is **on par with the individual GLiGuard and GLiNER2-PII models** on their respective tasks, letting you replace two models with one.