vault backup: 2024-09-29 17:23:51

.obsidian/workspace.json

@@ -13,7 +13,7 @@
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@@ -93,7 +93,7 @@
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@@ -110,7 +110,7 @@
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@@ -133,7 +133,7 @@
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@@ -175,8 +175,9 @@
   },
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   "lastOpenFiles": [
-    "Record/DL/Loss.md",
     "Record/DL/CoT Prompt.md",
+    "Record/DL/LLM.md",
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     "Paper/Diffusion/MoMA.md",
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@@ -211,7 +212,6 @@
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     "Books/Java Guide/基础语法.md",
     "Books/Java并发编程/Java并发编程.md",
-    "Books/从零开始深入学习Spring/IoC.md",
-    "Books/Vim实用技巧/一、入门导读.md"
+    "Books/从零开始深入学习Spring/IoC.md"
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 }

Record/DL/LLM.md

@@ -0,0 +1,5 @@
+## 常见超参
+- temperature
+	用于控制 LLM 输出的随机度。高热度更有创造性/难以预测，低热度则更为保守。
+- Top-K
+	即核心采样(nucleus smapling)，也是用处控制输出随机性的超参数。它设定了一个概率阈值，LLM 会选取累计概率超过该阈值的最佳词汇，然后 LLM 从这组词汇中随机抽取以生成输出。