Summary GitHub - dair-ai/Prompt-Engineering-Guide: Guide and resources for prompt engineering github.com
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The GitHub Prompt Engineering Guide provides a comprehensive overview of prompt engineering, including papers, tools, libraries, datasets, guides, tutorials, and other readings on topics such as deep learning, OpenAI Playground, GPTTools, Lexica, Prompt Base, and more.
Key Points
- GitHub's Prompt Engineering Guide provides comprehensive resources and learning materials for prompt engineering, including papers, tools & libraries, datasets, and blog posts.
- Topics discussed include surveys/overviews, pre-train, prompt, and predict methods, legal prompt engineering for multilingual legal judgement prediction, conversing with Copilot for CS1 problems, and Ask Me Anything prompting strategy.
- OpenAI Playground, GPTTools, Lexica, Prompt Base, PlaygroundOpenPrompt, Visual Prompt Builder, Prompt Generator for OpenAI's DALL-E2 AI Test Kitchen, Prompt Engine, PromptSourceShareGPT, PartiPrompts, Real Toxicity Prompts, DiffusionDBP3, WritingPrompts, Midjourney Prompts, Awesome ChatGPT Prompts, Stable Diffusion Dataset, Prompt Engineering by co:here and Microsoft, DALLE Prompt Book, DALL·E 2 Prompt Engineering Guide, Prompt Injection Attacks against GPT-3, Language Models and Prompt Engineering: Systematic Survey of Prompting Methods in NLPs, Extrapolating to Unnatural Language Processing with GPT-3's In-context Learning: The Good, the Bad and the Mysterious, Prompt Engineering Topic by GitHub, Prompt Engineering Template, NLP for Text-to-Image Generators: Prompt Analysis, GPT3 and Prompts: A Quick Primer, How to Draw Anything, Giving GPT-3 a Turing Test and How to Write Good Prompts are also discussed.
Summary
216 word summary
GitHub's Prompt Engineering Guide provides resources and learning materials for prompt engineering. It includes papers, tools & libraries, datasets, and blog posts. The guide covers surveys/overviews, pre-train, prompt, and predict methods, legal prompt engineering for multilingual legal judgement prediction, investigating prompt engineering in diffusion models, conversing with Copilot for CS1 problems, and Ask Me Anything prompting strategy. This guide provides a comprehensive overview of prompt engineering, which is a method of eliciting knowledge from language models with automatically generated prompts. It includes papers, tools and libraries, datasets, guides, tutorials, and other readings. Topics discussed include deep learning, prompt engineering, OpenAI Playground, GPTTools, Lexica, Prompt Base, PlaygroundOpenPrompt, Visual Prompt Builder, Prompt Generator for OpenAI's DALL-E2 AI Test Kitchen, Prompt Engine, PromptSourceShareGPT, PartiPrompts, Real Toxicity Prompts, DiffusionDBP3, WritingPrompts, Midjourney Prompts, Awesome ChatGPT Prompts, Stable Diffusion Dataset, Prompt Engineering by co:here and Microsoft, DALLE Prompt Book, DALL·E 2 Prompt Engineering Guide, Prompt Injection Attacks against GPT-3, Language Models and Prompt Engineering: Systematic Survey of Prompting Methods in NLPs, Extrapolating to Unnatural Language Processing with GPT-3's In-context Learning: The Good, the Bad and the Mysterious, Prompt Engineering Topic by GitHub, Prompt Engineering Template, NLP for Text-to-Image Generators: Prompt Analysis, GPT3 and Prompts: A Quick Primer, How to Draw Anything, Giving GPT-3 a Turing Test and How to Write Good Prompts.