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浏览 201 扫码 分享 2023-07-18 23:08:09
    • 【徹底解説】これからのエンジニアの必携スキル、プロンプトエンジニアリングの手引「Prompt Engineering Guide」を読んでまとめてみた(opens in a new tab)
    • 3 Principles for prompt engineering with GPT-3(opens in a new tab)
    • A beginner-friendly guide to generative language models - LaMBDA guide(opens in a new tab)
    • A Complete Introduction to Prompt Engineering for Large Language Models(opens in a new tab)
    • A Generic Framework for ChatGPT Prompt Engineering(opens in a new tab)
    • An SEO’s guide to ChatGPT prompts(opens in a new tab)
    • AI Content Generation(opens in a new tab)
    • AI’s rise generates new job title: Prompt engineer(opens in a new tab)
    • AI Safety, RLHF, and Self-Supervision - Jared Kaplan | Stanford MLSys #79(opens in a new tab)
    • Awesome Textual Instruction Learning Papers(opens in a new tab)
    • Awesome ChatGPT Prompts(opens in a new tab)
    • Best 100+ Stable Diffusion Prompts(opens in a new tab)
    • Best practices for prompt engineering with OpenAI API(opens in a new tab)
    • Building GPT-3 applications — beyond the prompt(opens in a new tab)
    • Can AI really be protected from text-based attacks?(opens in a new tab)
    • ChatGPT, AI and GPT-3 Apps and use cases(opens in a new tab)
    • ChatGPT Prompts(opens in a new tab)
    • CMU Advanced NLP 2022: Prompting(opens in a new tab)
    • Common Sense as Dark Matter - Yejin Choi | Stanford MLSys #78(opens in a new tab)
    • Create images with your words – Bing Image Creator comes to the new Bing(opens in a new tab)
    • Curtis64’s set of prompt gists(opens in a new tab)
    • DALL·E 2 Prompt Engineering Guide(opens in a new tab)
    • DALL·E 2 Preview - Risks and Limitations(opens in a new tab)
    • DALLE Prompt Book(opens in a new tab)
    • DALL-E, Make Me Another Picasso, Please(opens in a new tab)
    • Diffusion Models: A Practical Guide(opens in a new tab)
    • Exploiting GPT-3 Prompts(opens in a new tab)
    • Exploring Prompt Injection Attacks(opens in a new tab)
    • Extrapolating to Unnatural Language Processing with GPT-3’s In-context Learning: The Good, the Bad, and the Mysterious(opens in a new tab)
    • FVQA 2.0: Introducing Adversarial Samples into Fact-based Visual Question Answering(opens in a new tab)
    • Generative AI with Cohere: Part 1 - Model Prompting(opens in a new tab)
    • Generative AI: Perspectives from Stanford HAI(opens in a new tab)
    • Get a Load of This New Job: “Prompt Engineers” Who Act as Psychologists to AI Chatbots(opens in a new tab)
    • Giving GPT-3 a Turing Test(opens in a new tab)
    • GPT-3 & Beyond(opens in a new tab)
    • GPT3 and Prompts: A quick primer(opens in a new tab)
    • Hands-on with Bing’s new ChatGPT-like features(opens in a new tab)
    • How to Draw Anything(opens in a new tab)
    • How to get images that don’t suck(opens in a new tab)
    • How to make LLMs say true things(opens in a new tab)
    • How to perfect your prompt writing for AI generators(opens in a new tab)
    • How to write good prompts(opens in a new tab)
    • If I Was Starting Prompt Engineering in 2023: My 8 Insider Tips(opens in a new tab)
    • Indirect Prompt Injection on Bing Chat(opens in a new tab)
    • Interactive guide to GPT-3 prompt parameters(opens in a new tab)
    • Introduction to Reinforcement Learning with Human Feedback(opens in a new tab)
    • In defense of prompt engineering(opens in a new tab)
    • JailBreaking ChatGPT: Everything You Need to Know(opens in a new tab)
    • Language Models and Prompt Engineering: Systematic Survey of Prompting Methods in NLP(opens in a new tab)
    • Language Model Behavior: A Comprehensive Survey(opens in a new tab)
    • Learn Prompting(opens in a new tab)
    • Meet Claude: Anthropic’s Rival to ChatGPT(opens in a new tab)
    • Methods of prompt programming(opens in a new tab)
    • Mysteries of mode collapse(opens in a new tab)
    • NLP for Text-to-Image Generators: Prompt Analysis(opens in a new tab)
    • NLP with Deep Learning CS224N/Ling284 - Lecture 11: Promting, Instruction Tuning, and RLHF(opens in a new tab)
    • Notes for Prompt Engineering by sw-yx(opens in a new tab)
    • OpenAI Cookbook(opens in a new tab)
    • OpenAI Prompt Examples for several applications(opens in a new tab)
    • Pretrain, Prompt, Predict - A New Paradigm for NLP(opens in a new tab)
    • Prompt Engineer: Tech’s hottest job title?(opens in a new tab)
    • Prompt Engineering by Lilian Weng(opens in a new tab)
    • Prompt Engineering 101 - Introduction and resources(opens in a new tab)
    • Prompt Engineering 101: Autocomplete, Zero-shot, One-shot, and Few-shot prompting(opens in a new tab)
    • Prompt Engineering 101(opens in a new tab)
    • Prompt Engineering - A new profession ?(opens in a new tab)
    • Prompt Engineering by co:here(opens in a new tab)
    • Prompt Engineering by Microsoft(opens in a new tab)
    • Prompt Engineering: The Career of Future(opens in a new tab)
    • Prompt engineering davinci-003 on our own docs for automated support (Part I)(opens in a new tab)
    • Prompt Engineering Guide: How to Engineer the Perfect Prompts(opens in a new tab)
    • Prompt Engineering in GPT-3(opens in a new tab)
    • Prompt Engineering Template(opens in a new tab)
    • Prompt Engineering Topic by GitHub(opens in a new tab)
    • Prompt Engineering: The Ultimate Guide 2023 GPT-3 & ChatGPT
    • Prompt Engineering: From Words to Art(opens in a new tab)
    • Prompt Engineering with OpenAI’s GPT-3 and other LLMs(opens in a new tab)
    • Prompt injection attacks against GPT-3(opens in a new tab)
    • Prompt injection to read out the secret OpenAI API key(opens in a new tab)
    • Prompting: Better Ways of Using Language Models for NLP Tasks(opens in a new tab)
    • Prompting for Few-shot Learning(opens in a new tab)
    • Prompting in NLP: Prompt-based zero-shot learning(opens in a new tab)
    • Prompting Methods with Language Models and Their Applications to Weak Supervision(opens in a new tab)
    • Prompts as Programming by Gwern(opens in a new tab)
    • Prompts for communicators using the new AI-powered Bing(opens in a new tab)
    • Reverse Prompt Engineering for Fun and (no) Profit(opens in a new tab)
    • Retrieving Multimodal Information for Augmented Generation: A Survey(opens in a new tab)
    • So you want to be a prompt engineer: Critical careers of the future(opens in a new tab)
    • Simulators(opens in a new tab)
    • Start with an Instruction(opens in a new tab)
    • Talking to machines: prompt engineering & injection(opens in a new tab)
    • Tech’s hottest new job: AI whisperer. No coding required(opens in a new tab)
    • The Book - Fed Honeypot(opens in a new tab)
    • The ChatGPT Prompt Book(opens in a new tab)
    • The ChatGPT list of lists: A collection of 3000+ prompts, examples, use-cases, tools, APIs, extensions, fails and other resources(opens in a new tab)
    • The Most Important Job Skill of This Century(opens in a new tab)
    • The Mirror of Language(opens in a new tab)
    • The Waluigi Effect (mega-post)(opens in a new tab)
    • Thoughts and impressions of AI-assisted search from Bing(opens in a new tab)
    • Unleash Your Creativity with Generative AI: Learn How to Build Innovative Products!(opens in a new tab)
    • Unlocking Creativity with Prompt Engineering(opens in a new tab)
    • Using GPT-Eliezer against ChatGPT Jailbreaking(opens in a new tab)
    • What Is ChatGPT Doing … and Why Does It Work?

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    • 书签
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    • AIGC新手上路社群
    • 写给纯纯纯萌新
    • 课程体系说明
    • (说明)知识星球-信息架构
    • 启蒙篇:未来已来
      • GPT3的工作原理
      • 我们与AI时代
      • 写给萌新--关于chatGPT的一切
      • chatGPT只是个更智能的搜索工具?
      • ChatGPT并不能替代所有的能力
      • 从关系维度看待GPT
    • 认知篇:AIGC改变了哪里
      • gpt帮我“优化提示词”
      • gpt帮我“高效摄取知识”
      • gpt帮我做“产品设计”
    • 行动篇:从提问开始
      • 认识“关键词工程(Prompt)”
      • 向chatGPT提问,先解决认知
      • 提示词(Prompt)通用范式
      • 提示词(Prompt)范例
      • ChatGPT对话实例
      • 让AI帮我写测评多款AI的prompt
      • 让AI协助我做产品方案(极简Prompt)
      • 使用GPT"构建Prompt"
    • 工具篇:工欲善其事
      • ChatGPT3.5/4.0/Claude 横向测评
      • 讯飞星火/百度文心一言/阿里通义千问 横向测评
      • 讯飞星火认知大模型详解
      • ChatGPT官方插件入门
      • ChatGPT官方插件清单
      • 72款官方插件测评
      • 国内/外-大语言模型收录
      • 插件推荐- 伪装成GPT的notion
      • 插件推荐-沉浸式翻译
    • 启动篇:理解AIGC生成框架
      • 1. 内容生成场景
        • 1.1 文本生成
        • 1.4 语音生成
        • 1.5 视频生成
      • 2. 决策生成场景
        • 2.6 决策生成实战
      • 3. 行动指令生成场景
    • 案例篇:一个小白的AI成长之路
      • 案例篇:一个bingAI使用案例
    • AIGC进阶-Midjourney
      • 1.注册部署
      • 2.基础入门
      • 3.基本操作指令
      • 4.提示词入门
      • 5.参数详解
      • 6、实操案例
      • 7.课程总结
    • AIGC进阶-StableDiffusion超细节应用指北
      • 一、从安装开始,入门StableDiffusion【SD指北】
        • 第一节附录1 分享搭建Stable Diffusion的几种方法
      • 二、咒语!SD文生图的参数与提示词详解(SD指北)
    • AIGC进阶-Prompt Engineering深度学习
      • 1.提示工程简介
        • 1.1大语言模型设置
        • 1.2基本概念
        • 1.3提示词要素
        • 1.4设计提示的通用技巧
        • 1.5提示词示例
      • 2.提示技术
        • 2.5 生成知识提示
        • 2.6 自动提示工程师(APE)
        • 2.7 Active-Prompt
        • 2.8 方向性刺激提示
        • 2.9 ReAct框架
        • 2.10 多模态思维链提示方法
        • 2.11 GraphPrompts
      • 3.提示应用
        • 3.1 PAL(程序辅助语言模型)
        • 3.2 生成数据
        • 3.4 毕业生职位分类案例研究
      • 4.模型
        • 4.1 扩展指令微调语言模型(flan)
        • 4.2 ChatGPT提示工程
        • 4.3 LLaMA: 开放且高效的基础语言模型
        • 4.4 GPT-4
        • 附录:模型收录
      • 5.风险和误用
        • 5.1 对抗性提示
        • 5.2 真实性
        • 5.3 偏见
      • 6.工具和库
      • 7.实践笔记
      • 附录:数据集
      • 附录:推荐阅读
      • 附录:全球最新论文实时更新
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