翻译自: The Art of AI Prompt Crafting: A Comprehensive Guide for Enthusiasts引言欢迎来到人工智能的迷人世界以及制作有效提示的艺术!设计自然语言查询以引导模型输出朝向期望结果的过程通常被称为提示工程…
【OpenAI的提示工程(Prompt Engineering)指南】- 提示(Prompt)是给AI模型提供的额外上下文,可以增强模型的表现。 - 良好的提示可以让模型更好地理解任务要求,给出更相关和一致的响应。 - 提示通常包含任务描述、示例、条件等信息。 - 设计提示时需要考虑清晰度、避免歧义、提供足够示例等。
简单的任务从 CoT 的 prompt 中获益甚微。 CoT prompt 的类型 CoT prompt 的两种主要类型:few-shot CoT:通过一些演示来给模型 prompt,每个演示都包含人类编写(或模型生成)的高质量推理链。(所有数学推理例子均来自 GSM8k) Question: Tom and Elizabeth have a competition to climb a hill. Elizabeth takes 30 ...
How prompt engineering works Due to the way OpenAI models are trained, there are specific prompt formats that work particularly well and lead to more useful model outputs. The official prompt engineering guide by OpenAI is usually the best place to start for prompting tips. Below we present...
Prompt engineering 8 articles How do I create a good prompt for an AI model like GPT-4?Tips and suggestions to create great prompts for large language models Doing math with OpenAI modelsWhat are the challenges of trying to do math with OpenAI models and GPT-4? Using logit bias to alter...
得到更好结果的六个Prompt策略 一、编写清晰的说明 这些模型无法读懂你的想法。如果输出太长,请要求简短回复。如果结果太简单,就要求专家级的写作。如果您不喜欢格式,请演示您希望看到的格式。模型越少需要猜测您想要什么,您就越有可能得到它。 在您的询问中包含详细信息,以获得更多相关答案 ...
最近,有一篇论文《Code Generation with AlphaCodium: From Prompt Engineering to Flow Engineering》受到了各方的关注,特别是OpenAI技术大佬Andrej Karpathy对论文中提出的Flow engineering范式点评转发,将该论文热度推向了很高的位置。 它的核心思路是,利用多次生成测试反馈迭代的方式替代原有精心构造Prompt一次性生成的方...
基础PromptZero-shot 和 few-shot 学习是 prompt 模型的两种最基本的方法,许多关于 LLM 论文都有涉及,并常用于评估 LLM 的性能。Zero-Shot 学习Zero-Shot 学习是简单地将任务文本输入模型并要求其返回结果。(所有情感分析示例均来自 SST-2) Text: i'll bet the video game is a lot more fun than the film...
Prompt engineering and large language models are a fairly nascent field, so new ways to hack around them are being discovered every day. The two large classes of attacks are: Make the bot bypass any guidelines you have given it. Make the bot output hidden context that you didn’t intend ...
Prompt engineering often requires an iterative approach. Start with an initial prompt, review the response, and refine the prompt based on the output. Adjust the wording, add more context, or simplify the request as needed to improve the results. ...