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		<h1>Hướng dẫn kỹ thuật lời nhắc. Giới thiệu</h1>
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			<p align="justify"><b><span style="background: rgb(255, 255, 0);">Introduction</span></b></p>

<p align="justify">Theo: <a href="https://www.promptingguide.ai/introduction">https://www.promptingguide.ai/introduction</a></p>

<p align="justify">Kỹ thuật nhắc là một lĩnh vực tương đối mới trong việc phát triển và tối ưu hóa các lời nhắc để áp dụng và xây dựng hiệu quả với các mô hình ngôn ngữ lớn (LLM) cho nhiều ứng dụng và trường hợp sử dụng khác nhau.</p>

<p align="justify">Kỹ năng kỹ thuật nhắc giúp hiểu rõ hơn về khả năng và hạn chế của LLM. Các nhà nghiên cứu sử dụng kỹ thuật nhắc để cải thiện tính an toàn và khả năng của LLM trong nhiều tác vụ phổ biến và phức tạp như trả lời câu hỏi và lập luận số học. Các nhà phát triển sử dụng kỹ thuật nhắc để thiết kế các kỹ thuật nhắc nhở mạnh mẽ và hiệu quả, tương tác với LLM và các công cụ khác.</p>

<p align="justify">Hướng dẫn toàn diện này bao gồm các khía cạnh lý thuyết và thực hành của kỹ thuật nhắc nhở và cách tận dụng các kỹ thuật nhắc tốt nhất để tương tác và xây dựng với LLM.</p>

<p align="justify">Tất cả các ví dụ đều được kiểm tra với gpt-3.5-turbo bằng cách sử dụng <a href="https://platform.openai.com/playground">Sân chơi của OpenAI</a> trừ khi có quy định khác. Mô hình sử dụng các cấu hình mặc định, tức là temperature=1 và top_p=1. Các lời nhắc cũng sẽ hoạt động với các mô hình khác có khả năng tương tự như gpt-3.5-turbo nhưng phản hồi của mô hình có thể khác nhau.</p>

<ul>
	<li>
	<p align="justify"><a href="https://www.promptingguide.ai/introduction/settings">Thiết lập LLM</a></p>
	</li>
	<li>
	<p align="justify"><a href="https://www.promptingguide.ai/introduction/basics">Cơ bản về lời nhắc</a></p>
	</li>
	<li>
	<p align="justify"><a href="https://www.promptingguide.ai/introduction/elements">Các thành phần của lời nhắc</a></p>
	</li>
	<li>
	<p align="justify"><a href="https://www.promptingguide.ai/introduction/tips">Mẹo chung để thiết kế lời nhắc</a></p>
	</li>
	<li>
	<p align="justify"><a href="https://www.promptingguide.ai/introduction/examples">Ví dụ về lời nhắc</a></p>
	</li>
</ul>

<p align="justify"><a href="https://giaoducmo.avnuc.vn/ai/huong-dan-ky-thuat-loi-nhac-1569.html">Về mục lục</a> ………. Phần tiếp theo</p>

<p align="justify"><span style="background: rgb(255, 255, 0);">Prompt engineering is a relatively new discipline for developing and optimizing prompts to efficiently apply and build with large language models (LLMs) for a wide variety of applications and use cases.</span></p>

<p align="justify"><span style="background: rgb(255, 255, 0);">Prompt engineering skills help to better understand the capabilities and limitations of LLMs. Researchers use prompt engineering to improve safety and the capacity of LLMs on a wide range of common and complex tasks such as question answering and arithmetic reasoning. Developers use prompt engineering to design robust and effective prompting techniques that interface with LLMs and other tools.</span></p>

<p align="justify"><span style="background: rgb(255, 255, 0);">This comprehensive guide covers the theory and practical aspects of prompt engineering and how to leverage the best prompting techniques to interact and build with LLMs.</span></p>

<p align="justify"><span style="background: rgb(255, 255, 0);">All examples are tested with </span><code class="western"><span style="background: rgb(255, 255, 0);">gpt-3.5-turbo</span></code><span style="background: rgb(255, 255, 0);"> using the <a href="https://platform.openai.com/playground" target="_blank">OpenAI&#039;s Playground</a> unless otherwise specified. The model uses the default configurations, i.e., </span><code class="western"><span style="background: rgb(255, 255, 0);">temperature=1</span></code><span style="background: rgb(255, 255, 0);"> and </span><code class="western"><span style="background: rgb(255, 255, 0);">top_p=1</span></code><span style="background: rgb(255, 255, 0);">. The prompts should also work with other models that have similar capabilities as </span><code class="western"><span style="background: rgb(255, 255, 0);">gpt-3.5-turbo</span></code><span style="background: rgb(255, 255, 0);"> but the model responses may vary.</span></p>

<ul>
	<li>
	<p align="justify"><a href="https://www.promptingguide.ai/introduction/settings"><span style="background: rgb(255, 255, 0);">LLM Settings</span></a></p>
	</li>
	<li>
	<p align="justify"><span style="background: rgb(255, 255, 0);"><a href="https://www.promptingguide.ai/introduction/basics">Basics of Prompting</a> </span></p>
	</li>
	<li>
	<p align="justify"><span style="background: rgb(255, 255, 0);"><a href="https://www.promptingguide.ai/introduction/elements">Prompt Elements</a> </span></p>
	</li>
	<li>
	<p align="justify"><a href="https://www.promptingguide.ai/introduction/tips"><span style="background: rgb(255, 255, 0);">General Tips for Desig</span></a><span style="background: rgb(255, 255, 0);"><a href="https://www.promptingguide.ai/introduction/tips">ning Prompts</a> </span></p>
	</li>
	<li>
	<p align="justify"><span style="background: rgb(255, 255, 0);"><a href="https://www.promptingguide.ai/introduction/examples">Examples of Prompts</a> </span></p>
	</li>
</ul>

<p align="justify">Dịch: Lê Trung Nghĩa</p>

<p align="justify">letrungnghia.foss@gmail.com</p>
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