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 ---
-title: "Transformer"
+title: Transformer
 tags:
-- deep-learning
-- attention
-date: 2024-01-17
+  - deep-learning
+  - attention
+date: 2024-10-09
 ---
 
 > [!info] 
@@ -18,4 +18,15 @@ Transformer 是Seq2Seq model，由Encoder和Decoder组成
 这里贴的是原文Encoder的架构
 ![Pasted image 20230316162635](computer_sci/deep_learning_and_machine_learning/deep_learning/attachments/Pasted%20image%2020230316162635.png)
 
-![Pasted image 20230316162642](computer_sci/deep_learning_and_machine_learning/deep_learning/attachments/Pasted%20image%2020230316162642.png)
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+![Pasted image 20230316162642](computer_sci/deep_learning_and_machine_learning/deep_learning/attachments/Pasted%20image%2020230316162642.png)
+
+
+## Learn by Animation Demo
+
+2024 VIS poster session 里有一个海报介绍的Transformer Explainer太清晰了，包含word embedding，QKV到attention的计算，dropout， layer normalization ... ... 
+
+通过这个demo可以清晰地理解LLM中Transformer模块地应用
+
+访问：[https://poloclub.github.io/transformer-explainer/](https://poloclub.github.io/transformer-explainer/)
+
+![](computer_sci/deep_learning_and_machine_learning/deep_learning/attachments/Pasted%20image%2020241010112210.png)
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