OpenAI发布了Privacy Filter模型卡，能高效处理文本隐私信息，效果比传统方案更专业。
OpenAI推出的Privacy Filter模型卡，该模型有1.5亿总参数，用于检测和红action文本中的个人身份信息；该模型通过单次前向传递标注输入序列，支持12800 - 词上下文窗口；它能配置操作点平衡精确率与召回率，涵盖八类隐私分类。
Model Card for OpenAI Privacy Filter
OpenAI Privacy Filter is a compact, bidirectional token-classification model for detecting and redacting personally identifiable information (PII) and secrets in unstructured text. The model is derived from an autoregressively pretrained checkpoint and converted into a bidirectional, banded-attention classifier that labels an input sequence in a single forward pass. A constrained Viterbi decoder produces coherent spans across eight privacy categories and exposes configurable operating points for precision-recall tradeoffs. Privacy Filter has 1.5 billion total parameters, 50 million active parameters per token, and a 128,000-token context window. It is designed for efficient local deployment and domain-specific fine-tuning. Privacy Filter is intended as a configurable data-minimization component within layered privacy workflows, not as an anonymization or compliance guarantee.