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Company behind GLiNER model released open source model for running LLM guardrail

Fastino Labs introduces GLiGuard, a 300 million parameter open source small language model for safety moderation. It reframes safety moderation as a classification problem, evaluating multiple safety dimensions in a single pass, and achieves up to 16x faster speed than current state-of-the-art decoder models while matching accuracy of models 23 to 90 times its size.

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Company behind GLiNER model released open source model for running LLM guardrail
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Key points

  • GLiGuard is a 300M parameter encoder model that treats safety moderation as text classification rather than generation.
  • It handles four moderation tasks concurrently in one forward pass: safety classification, jailbreak detection, harm category detection, and refusal detection.
  • Across nine safety benchmarks, GLiGuard matches the accuracy of models 23-90x larger while running up to 16x faster.
  • Model weights are open-sourced under Apache 2.0 on Hugging Face Hub.

Highlights and analysis are generated automatically and may contain errors. Check the original source.

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