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OpenAI open-sources Privacy Filter, which can automatically detect and mask private information in text locally.

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ME News, April 23 (UTC+8), according to Beating monitoring, OpenAI open-sourced the Privacy Filter under the Apache 2.0 license, a locally deployed text desensitization model. When users input text into the model, it automatically identifies and marks or masks eight categories of personally identifiable information (PII): names, email addresses, phone numbers, addresses, account numbers, URLs, dates, and keys. The entire process runs locally, and data does not need to be sent to the cloud. The model has a total of 1.5B parameters, but adopts a sparse mixture-of-experts architecture, so only 50M parameters are activated per inference, allowing it to run on laptops or even in a browser. With a context window of 128K tokens, all privacy information can be labeled in a single forward pass. Users can adjust the trade-off between precision and recall via preset operating points, and can also fine-tune the model with their own data to adapt to specific scenarios. The model is primarily English-based, with limited multilingual capabilities. (Source: BlockBeats)
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