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English(EN) An official 1-bit quant for Hy4??? 👀

HY4 语言模型实现 1 位量化,准确性损失极小

HY4 语言模型发布了新的 1 位量化技术,与 BF16 相比,准确性损失极小,显示出有希望的结果。该量化最初被错误标记为 Q1,但实际上是 2.38 位,在 MCP AtlasSWE-BenchMRCRIFBench 等基准测试中保持了高分。此举旨在通过降低内存需求,使大型语言模型更加易于访问。 AI

影响 通过减少内存占用,能够更有效地部署大型语言模型,可能提高其可访问性。

排序理由 该条目讨论了一种现有语言模型的新量化方法,这是一项技术研究进展。[lever_c_demoted from research: ic=1 ai=1.0]

在 r/LocalLLaMA 阅读 →

AI 生成摘要 · Google Gemini · 来自 1 个来源。 我们如何撰写摘要 →

HY4 语言模型实现 1 位量化,准确性损失极小

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该条目讨论了一种现有语言模型的新量化方法,这是一项技术研究进展。[lever_c_demoted from research: ic=1 ai=1.0]
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model release
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报道来源 [1]

  1. r/LocalLLaMA TIER_1 English(EN) · /u/lakySK ·

    Hy4 的官方 1 位量化???👀

    <table> <tr><td> <a href="https://www.reddit.com/r/LocalLLaMA/comments/1w1kt83/an_official_1bit_quant_for_hy4/"> <img alt="An official 1-bit quant for Hy4??? 👀" src="https://external-preview.redd.it/FlcMFmYMZTv14oNtDNvQYc45O-kKtdEF6wcQrZkR3Pk.png?width=640&amp;crop=smart&amp;auto…