Protegrity发布2.78亿参数开放权重PII检测模型
Protegrity宣布了一款2.78亿参数的开放权重PII检测模型、配套脚本、PII-SCOPE基准和研究论文。开发者称，该RoBERTa微调模型使用12亿个包含多种PII的合成文本样本训练，可根据上下文识别PII实例，返回每个实例的索引和类型，或对检测到的全部PII进行脱敏。PII-SCOPE旨在解决公开LLM生成数据集中的常见问题，并已在Hugging Face上提供。
此次发布提供了用于识别和脱敏PII的开放权重模型与参考基准，其中PII-SCOPE旨在解决公开LLM生成数据集中发现的问题。
Hi everyone,
I wanted to share a new open-weights PII detection model, benchmark and research paper. It's a fine-tune of RoBERTa using 1.2B samples of synthetically generated text that contain a variety of PII. The benchmark, PII-SCOPE (Synthetic Context and Ontology for PII Extraction), was built to address common issues in public LLM-generated datasets and is on Hugging Face too. The model and script identify instances of PII based on surrounding context, and then return the index and type of each instance. Alternatively, it can return the input with all PII redacted.
Technical report (research paper) https://arxiv.org/html/2610.30518v2
Hugging Face model card https://huggingface.co/Protegrity/protegrity-pii
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#Protegrity#Protegrity PII Detection Model#RoBERTa#PII-SCOPE#Hugging Face