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如何用0.2%训练提升405B大模型的线性注意力?
在这个不断变化的科技世界中,人工智能的进步从未停止。最近,斯坦福大学与麻省理工学院的研究团队又一次惊艳了我们,推出了一种名为LoLCATs(低秩线性转换与注意力转移)的新方法,让训练405B大模型的线性化成为现实。这项技术的核心在于,仅通过0.2%的参数更新,就能显著提高模型的性能,令人瞩目的提升幅度甚至突破了20分!
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