@hank_aibtc: Holy crap, OpenAI finally did something good!!! The first open-source model of 2026 is here – Privacy Filter, released under Apache 2.0! A 1.5B parameter PII detection tool, specifically for redacting names, addresses, phone numbers, emails, IDs, etc. from text…

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Summary

OpenAI open-sourced the Privacy Filter model (1.5B parameters, Apache 2.0), which runs locally in the browser via WebGPU to detect personal information without uploading data, protecting privacy.

Holy crap, OpenAI finally did something good!!! The first open-source model of 2026 is here – Privacy Filter, released under Apache 2.0! A 1.5B parameter PII detection tool, specifically for redacting sensitive information like names, addresses, phone numbers, emails, and ID numbers from text instantly. The key is that it runs locally in your browser, using WebGPU, no need to send anything to a server! Core highlights: 1. Multilingual support 2. Fully local operation (Transformers.js + WebGPU), no server upload needed, usable directly in the browser 3. Real-time document processing, privacy-first Suitable for compliance audits, user data processing, local privacy workflows, etc. The demo is very smooth, especially for teams and developers requiring strong privacy guarantees. Link in comments
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Cached at: 05/27/26, 07:19 AM

Wow! OpenAI finally did something right!!!

The first open-source model of 2026 is here — Privacy Filter,
released under Apache 2.0 directly!

A 1.5B parameter PII (Personal Identifiable Information) detection tool,
specializing in instantly redacting sensitive info from text: names, addresses, phone numbers, emails, ID numbers, and more.

The key is it runs locally in your browser, using WebGPU directly —
no need to send anything to a server!

Core highlights:

  1. Multilingual support
  2. Fully local execution (Transformers.js + WebGPU), no upload to server, works right in the browser
  3. Real-time document processing with privacy-first approach

Perfect for compliance audits,
user data processing, local privacy workflows, and similar use cases.

The demo is very smooth, especially suited for teams and developers who need strong privacy guarantees.

Link in comments.

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