Lilian Weng 更新了她关于 Transformer 架构及其自推出以来的众多进展的详细博文。更新后的版本“Transformer 系列 2.0 版”在原版的基础上进行了大量扩展，整合了最新的研究和对基础模型的修改。它深入探讨了注意力机制、自注意力机制、多头自注意力机制以及编码器-解码器结构等核心概念，详细概述了这些组件的功能及其改进之处。 AI
排序理由 博文总结和更新 Transformer 架构的研究。
AI 生成摘要 · Google Gemini · 来自 2 个来源。 我们如何撰写摘要 →
<p>Many new Transformer architecture improvements have been proposed since my last post on <a href="https://lilianweng.github.io/posts/2020-04-07-the-transformer-family/"><ins>“The Transformer Family”</ins></a> about three years ago. Here I did a big refactoring and e…
<!-- Inspired by recent progress on various enhanced versions of Transformer models, this post presents how the vanilla Transformer can be improved for longer-term attention span, less memory and computation consumption, RL task solving, etc. --> <p><span class="update">[Updated …