From 0eea57b11f88ce21129b76f7be7e0558b2e048a6 Mon Sep 17 00:00:00 2001
From: KMnO4-zx <1021385881@qq.com>
Date: Fri, 20 Jun 2025 15:04:23 +0800
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diff --git a/docs/chapter2/第二章 Transformer架构.md b/docs/chapter2/第二章 Transformer架构.md
index c725cde..d3915b0 100644
--- a/docs/chapter2/第二章 Transformer架构.md	
+++ b/docs/chapter2/第二章 Transformer架构.md	
@@ -568,7 +568,7 @@ class Decoder(nn.Module):
 
 在前两章，我们分别深入剖析了 Attention 机制和 Transformer 的核心——Encoder、Decoder 结构，接下来，我们就可以基于上一章实现的组件，搭建起一个完整的 Transformer 模型。
 
-### 2.3.1 Embeddng 层
+### 2.3.1 Embedding 层
 
 正如我们在第一章所讲过的，在 NLP 任务中，我们往往需要将自然语言的输入转化为机器可以处理的向量。在深度学习中，承担这个任务的组件就是 Embedding 层。