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On-device, no-code LLMs with guardrails (for Apple Silicon)

Show HN: On-device, no-code LLMs with guardrails (for Apple Silicon)

On-device, no-code LLMs with guardrails (for Apple Silicon) is a business in show hn launch.

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We've been working to make uncertainty quantification and interpretability first-class properties of LLMs. Reexpress one, a macOS app, is our first effort to make these properties widely available.Perhaps counter-intuitively, and contrary to common wisdom, LLMs can in fact be transformed to generate very reliable uncertainty estimates (i.e., "knowing what they do and don't know" by assigning a probability to the output).Getting there is a bit complicated, with vector matching/databases, prediction-time data dependencies, complicated inference, and multiple models flying all over the place.We've made it simple and efficient to use in practice with an on-device, no-code approach. Common docume

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Website: re.express

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