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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: On April 23 (UTC+8), according to Dongcha Beating monitoring, OpenAI open-sourced Privacy Filter under the Apache 2.0 license, a locally deployed text de-identification model. Users input text into the model, and it automatically recognizes eight categories of personally identifiable information (PII): names, email addresses, phone numbers, addresses, account numbers, URLs, dates, and keys, and then marks or masks them. The entire process is completed locally, and the data does not need to be sent to the cloud. The model has a total of 1.5B parameters, but uses a sparse mixture-of-experts architecture, so only 50M parameters are activated per inference. Therefore, it can run on laptops or even in a browser. With a context window of 128K tokens, a single forward pass can label all privacy information. Users can adjust the tradeoff between precision and recall through preset operation points, or fine-tune the model with their own data to fit specific scenarios. The model is primarily English-focused, with limited multilingual capabilities. (Source: BlockBeats)
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