<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom">
  <channel>
    <title>Chain of Prompt on GPT资讯  --  知识铺</title>
    <link>https://index.zshipu.com/gpt/tags/Chain-of-Prompt/</link>
    <description>Recent content in Chain of Prompt on GPT资讯  --  知识铺</description>
    <generator>Hugo -- gohugo.io</generator>
    <language>zh-CN</language>
    <lastBuildDate>Wed, 27 Mar 2024 15:30:08 +0000</lastBuildDate>
    <atom:link href="https://index.zshipu.com/gpt/tags/Chain-of-Prompt/index.xml" rel="self" type="application/rss+xml" />
    <item>
      <title>Prompt Engineering Techniques for Improving ChatGPT Responses</title>
      <link>https://index.zshipu.com/gpt/post/20240328/Prompt-Engineering-Techniques-for-Improving-ChatGPT-Responses--%E7%9F%A5%E8%AF%86%E9%93%BA/</link>
      <pubDate>Wed, 27 Mar 2024 15:30:08 +0000</pubDate>
      <guid>https://index.zshipu.com/gpt/post/20240328/Prompt-Engineering-Techniques-for-Improving-ChatGPT-Responses--%E7%9F%A5%E8%AF%86%E9%93%BA/</guid>
      <description>简介 Prompt(提示)，最初是 NLP 研究者为下游任务设计出来的一种任务专属的输入形式或模板。在 ChatGPT 引发大语言模型新时代之后，Prompt 指与大模型交互输入的代称。 随着大模型的进展，Prompt Engineering是一个持久的探索过程。本文主要概括了我前段时间学习prompt的一些心</description>
    </item>
  </channel>
</rss>
