kevinamiri/Instructgpt-prompts

• highreadme#1

  Reposition README opening to clarify repo's purpose

  原因：

  当前

  InstructGPT were the first series of language models that had been trained using supervised fine-tuning on top of the base model.

  复制粘贴的修复

  复制

  # Instruction-following prompts for GPT-instruct, GPT-3.5
  
  This repository provides a curated collection of instruction-following prompts and strategies specifically designed for GPT-instruct and GPT-3.5 models. It aims to help users optimize language model interactions through zero-shot prompting techniques, addressing common challenges like phrasing and position sensitivity.
  
  InstructGPT were the first series of language models that had been trained using supervised fine-tuning on top of the base model.

  待办完成忽略
• mediumtopics#2

  Add more specific prompt engineering topics

  原因：

  当前

  chatgpt, chatgpt-prompts, gpt-3, gpt-3-prompt, gpt-3-prompts, gpt-35, gpt-35-prompts, gpt-4, gpt3, gpt3-instruct, gpt35, gpt4, instruct-gpt, instructgpt, instruction-following, prompt-engineering, prompting, zero-shot-prompts

  复制粘贴的修复

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  chatgpt, chatgpt-prompts, gpt-3, gpt-3-prompt, gpt-3-prompts, gpt-35, gpt-35-prompts, gpt-4, gpt3, gpt3-instruct, gpt35, gpt4, instruct-gpt, instructgpt, instruction-following, prompt-engineering, prompting, zero-shot-prompts, prompt-optimization, llm-prompts, ai-prompts, prompt-design

  待办完成忽略
• mediumreadme#3

  Add a section differentiating this collection from general prompt guides

  原因：

  复制粘贴的修复

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  ## Why use this collection?
  
  While comprehensive resources like OpenAI's Prompt Engineering Guide offer broad principles, this repository provides a focused, curated collection of prompts and strategies specifically tailored for GPT-instruct and GPT-3.5. It emphasizes practical application and deep dives into challenges like phrasing and position sensitivity, offering ready-to-use examples rather than just theoretical advice.

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  How to write effective prompts for large language models to improve text generation?

  你：未被推荐
  AI 推荐顺序：

  1. OpenAI Playground
  2. OpenAI API
  3. GPT-4
  4. Claude 3 Opus
  5. Google Gemini Advanced
  6. GPT-3.5 Turbo
  7. Claude 3 Sonnet
  8. Llama 3
  9. Anthropic API
  10. Google AI Studio

  AI 推荐了 10 个替代方案，却始终没点名 kevinamiri/Instructgpt-prompts。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  Seeking strategies to improve language model accuracy by optimizing prompt phrasing and position.

  你：未被推荐
  AI 推荐顺序：

  1. OpenAI's Prompt Engineering Guide
  2. Google's Prompt Design Guide
  3. LearnPrompting.org
  4. Awesome Prompt Engineering
  5. LangChain
  6. LlamaIndex
  7. Weights & Biases (W&B Prompts)
  8. Humanloop

  AI 推荐了 8 个替代方案，却始终没点名 kevinamiri/Instructgpt-prompts。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  pass

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of kevinamiri/Instructgpt-prompts?

  pass
  ✓AI 明确点名了 kevinamiri/Instructgpt-prompts

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts kevinamiri/Instructgpt-prompts in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 kevinamiri/Instructgpt-prompts

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo kevinamiri/Instructgpt-prompts solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 kevinamiri/Instructgpt-prompts

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？