Mastering Prompt Engineering for LLMs: Chain of Thought( CoT), Tree of thought( ToT), and Self-reflection
Vemula, Anand
- 出版商: Independently Published
- 出版日期: 2024-05-09
- 售價: $1,000
- 貴賓價: 9.5 折 $950
- 語言: 英文
- 頁數: 36
- 裝訂: Quality Paper - also called trade paper
- ISBN: 9798325211713
- ISBN-13: 9798325211713
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相關分類:
LangChain
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商品描述
Mastering Prompt Engineering for LLMs: CoT, ToT, and Self-Reflection dives into the world of Large Language Models (LLMs) and explores a powerful technique called prompt engineering. This book equips you to unlock the true potential of LLMs by guiding them through complex tasks and reasoning processes.
Part 1 lays the foundation by explaining how LLMs work and the importance of prompt design. It introduces Chain of Thought (CoT) prompting, a step-by-step approach for guiding LLMs through logical reasoning.
Part 2 delves into Tree of Thought (ToT) prompting, enabling LLMs to explore multiple possibilities and weigh evidence before reaching a conclusion. You'll learn how to craft ToT prompts to tackle open-ended tasks and spark creative problem-solving.
Part 3 introduces the concept of self-reflection in LLMs. By crafting prompts that encourage LLMs to analyze their reasoning process, you can enhance the accuracy, reliability, and trustworthiness of their outputs.
Part 4 explores the exciting future of prompt engineering. It discusses emerging trends like few-shot learning prompts and interactive prompting techniques that allow for real-time adaptation during LLM interactions. You'll also delve into the ethical considerations of advanced prompt engineering, ensuring responsible use of this powerful technology.
Through case studies, use cases, and clear explanations, this book empowers you to become a skilled prompt engineer, unlocking the full potential of LLMs in various fields, from scientific discovery and education to creative writing and marketing.
商品描述(中文翻譯)
《精通 LLM 的提示工程:CoT、ToT 和自我反思》深入探索了大型語言模型(LLMs)的世界,並探討了一種強大的技術,稱為提示工程。本書將引導您通過複雜的任務和推理過程,解鎖 LLMs 的真正潛力。
第一部分奠定了基礎,解釋了 LLMs 的工作原理以及提示設計的重要性。它介紹了思維鏈(CoT)提示,這是一種逐步引導 LLMs 進行邏輯推理的方法。
第二部分深入探討了思維樹(ToT)提示,使 LLMs 能夠探索多種可能性並在得出結論之前權衡證據。您將學習如何製作 ToT 提示,以應對開放性任務並激發創造性問題解決能力。
第三部分介紹了 LLMs 中的自我反思概念。通過製作鼓勵 LLMs 分析其推理過程的提示,您可以提高其輸出的準確性、可靠性和可信度。
第四部分探索了提示工程的令人興奮的未來。它討論了新興趨勢,如少樣本學習提示和互動提示技術,允許在 LLM 交互過程中進行實時適應。您還將深入探討高級提示工程的道德考慮,確保負責任地使用這項強大的技術。
通過案例研究、應用案例和清晰的解釋,本書使您能夠成為一名熟練的提示工程師,在科學發現、教育、創意寫作和市場營銷等各個領域中充分發揮 LLMs 的潛力。