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@@ -20,6 +20,10 @@ pair it predicts `{entailment, neutral, contradiction}`. Fine-tuned from
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  then exported to ONNX and **dynamically quantized to int8** (per-channel,
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  avx512_vnni) for portable CPU inference.
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  **GitHub:** [Arthur920/Staleguard](https://github.com/Arthur920/Staleguard) 路
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  **Docs:** [arthur920.github.io/Staleguard](https://arthur920.github.io/Staleguard/)
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  then exported to ONNX and **dynamically quantized to int8** (per-channel,
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  avx512_vnni) for portable CPU inference.
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+ Please note that the ml drift detection approach is undergoing quite some change.
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+
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+ Take a look at the Github Project below for a deterministic fast and lightweight documentation drift detection layer on which this model intends to build.
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  **GitHub:** [Arthur920/Staleguard](https://github.com/Arthur920/Staleguard) 路
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  **Docs:** [arthur920.github.io/Staleguard](https://arthur920.github.io/Staleguard/)
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