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| <link rel="modulepreload" href="/docs/course/pr_1021/zh-CN/_app/immutable/chunks/getInferenceSnippets.ebf8be91.js"><!-- HEAD_svelte-u9bgzb_START --><meta name="hf:doc:metadata" content="{"title":"本章简介","local":"本章简介","sections":[{"title":"欢迎来到🤗 Hugging Face 课程","local":"欢迎来到🤗 Hugging Face 课程","sections":[],"depth":2},{"title":"有什么是值得期待的？","local":"有什么是值得期待的？","sections":[],"depth":2},{"title":"我们是谁？","local":"我们是谁？","sections":[],"depth":2},{"title":"FAQ","local":"faq","sections":[],"depth":2},{"title":"让我们开始吧！","local":"让我们开始吧！","sections":[],"depth":2}],"depth":1}"><!-- HEAD_svelte-u9bgzb_END --> <p></p> <h1 class="relative group"><a id="本章简介" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#本章简介"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>本章简介</span></h1> <div class="flex space-x-1 absolute z-10 right-0 top-0"><a href="https://discuss.huggingface.co/t/chapter-1-questions" target="_blank"><img alt="Ask a Question" class="!m-0" src="https://img.shields.io/badge/Ask%20a%20question-ffcb4c.svg?logo=data:image/svg+xml;base64,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"></a> </div> <h2 class="relative group"><a id="欢迎来到🤗 Hugging Face 课程" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#欢迎来到🤗 Hugging Face 课程"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>欢迎来到🤗 Hugging Face 课程</span></h2> <iframe class="w-full xl:w-4/6 h-80" src="https://www.youtube-nocookie.com/embed/00GKzGyWFEs" title="YouTube video player" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe> <p data-svelte-h="svelte-128b55u">本课程将教你如何使用 Hugging Face 生态系统的库进行自然语言处理（NLP）。这些库包括 🤗 Transformers、🤗 Datasets、🤗 Tokenizers 和 🤗 Accelerate，以及 Hugging Face Hub。本课程完全免费且无广告。</p> <h2 class="relative group"><a id="有什么是值得期待的？" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#有什么是值得期待的？"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>有什么是值得期待的？</span></h2> <p data-svelte-h="svelte-13xvk27">以下是课程的简要概述：</p> <div class="flex justify-center" data-svelte-h="svelte-1f838r7"><img class="block dark:hidden" src="https://huggingface.co/datasets/huggingface-course/documentation-images/resolve/main/en/chapter1/summary.svg" alt="Brief overview of the chapters of the course."> <img class="hidden dark:block" src="https://huggingface.co/datasets/huggingface-course/documentation-images/resolve/main/en/chapter1/summary-dark.svg" alt="Brief overview of the chapters of the course."></div> <ul data-svelte-h="svelte-a3h3vw"><li>第 1 章到第 4 章介绍了 🤗 Transformers 库的主要概念。在本课程的这一部分结束时，你将了解 Transformer 模型的工作原理，并将了解如何使用 <a href="https://huggingface.co/models" rel="nofollow">Hugging Face Hub</a> 中的模型，在数据集上对其进行微调，并在 Hub 上分享你的结果。</li> <li>第 5 章到第 8 章在深入研究经典 NLP 任务之前，教授 🤗 Datasets 和 🤗 Tokenizers 的基础知识。在本部分结束时，你将能够自己解决最常见的 NLP 问题。</li> <li>第 9 章到第 12 章将超越 NLP，探讨如何使用 Transformer 模型解决语音处理和计算机视觉任务。在此过程中，你将学习如何构建和分享模型的演示，并将它们优化为生产环境。完成这部分课程后，你将准备好将 🤗 Transformers 应用于（几乎）任何机器学习问题！</li></ul> <p data-svelte-h="svelte-18iju9i">这个课程：</p> <ul data-svelte-h="svelte-15hovv3"><li>需要良好的 Python 知识</li> <li>在完成入门深度学习课程后效果更佳，例如 <a href="https://www.deeplearning.ai/" rel="nofollow">DeepLearning.AI</a> 提供的 <a href="https://course.fast.ai/" rel="nofollow">fast.ai实用深度学习教程</a></li> <li>不需要事先具备 <a href="https://pytorch.org/" rel="nofollow">PyTorch</a> 或 <a href="https://www.tensorflow.org/" rel="nofollow">TensorFlow</a> 知识，虽然熟悉其中任何一个都会对学习有所帮助</li></ul> <p data-svelte-h="svelte-1m1iabr">完成本课程后，我们建议你查看 <a href="https://www.coursera.org/specializations/natural-language-processing?utm_source=deeplearning-ai&utm_medium=institutions&utm_campaign=20211011-nlp-2-hugging_face-page-nlp-refresh" rel="nofollow">DeepLearning.AI的自然语言处理系列课程</a> ，该课程涵盖了诸如朴素贝叶斯和 LSTM 等传统 NLP 模型的广泛内容，非常值得了解！</p> <h2 class="relative group"><a id="我们是谁？" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#我们是谁？"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>我们是谁？</span></h2> <p data-svelte-h="svelte-1791w9c">关于作者：</p> <p data-svelte-h="svelte-yfudws"><a href="https://huggingface.co/abidlabs" rel="nofollow"><strong>Abubakar Abid</strong></a> 在斯坦福大学获得应用机器学习博士学位。在攻读博士学位期间，他创立了 <a href="https://github.com/gradio-app/gradio" rel="nofollow">Gradio</a> ，这是一个开源 Python 库，已用于构建超过 600,000 个机器学习演示。Gradio 被 Hugging Face 收购，Abubakar 现在在 Hugging Face 担任机器学习团队负责人。</p> <p data-svelte-h="svelte-16y3ebe"><a href="https://huggingface.co/Rocketknight1" rel="nofollow"><strong>Matthew Carrigan</strong></a> 是 Hugging Face 的机器学习工程师。他住在爱尔兰都柏林，之前在 Parse.ly 担任机器学习工程师，在此之前，他在 Trinity College Dublin 担任博士后研究员。他不相信我们会通过扩展现有架构来实现 AGI，但仍然对机器人永生抱有很高的期望。</p> <p data-svelte-h="svelte-5w8uc3"><a href="https://huggingface.co/lysandre" rel="nofollow"><strong>Lysandre Debut</strong></a> 是 Hugging Face 的机器学习工程师，从早期的开发阶段就一直致力于 🤗 Transformers 库。他的目标是通过使用非常简单的 API 开发工具，让 NLP 对每个人都变得易用。</p> <p data-svelte-h="svelte-14ru7m"><a href="https://huggingface.co/sgugger" rel="nofollow"><strong>Sylvain Gugger</strong></a> 是 Hugging Face 的一名研究工程师，也是 🤗Transformers 库的核心维护者之一。此前，他是 fast.ai 的一名研究科学家，他与 Jeremy Howard 共同编写了 <a href="https://learning.oreilly.com/library/view/deep-learning-for/9781492045519/" rel="nofollow">Deep Learning for Coders with fastai and Py Torch</a> 。他的研究重点是通过设计和改进技术，使模型在有限资源上进行快速训练，使深度学习更容易普及。</p> <p data-svelte-h="svelte-5qp3w1"><a href="https://huggingface.co/dawoodkhan82" rel="nofollow"><strong>Dawood Khan</strong></a> 是 Hugging Face 的机器学习工程师。他来自纽约，毕业于纽约大学计算机科学专业。在担任 iOS 工程师几年后，Dawood 辞职并与其他联合创始人一起创办了 Gradio。Gradio 最终被 Hugging Face 收购。</p> <p data-svelte-h="svelte-l96prq"><a href="https://huggingface.co/sgugger" rel="nofollow"><strong>Merve Noyan</strong></a> 是 Hugging Face 的开发者倡导者，致力于开发工具并围绕它们构建内容，以使每个人都可以使用机器学习。</p> <p data-svelte-h="svelte-1xuo5ha"><a href="https://huggingface.co/SaulLu" rel="nofollow"><strong>Lucile Saulnier</strong></a> 是 Hugging Face 的机器学习工程师，负责开发和支持开源工具的使用。她还积极参与了自然语言处理领域的许多研究项目，例如协作训练和 BigScience。</p> <p data-svelte-h="svelte-6zllsx"><a href="https://huggingface.co/lewtun" rel="nofollow"><strong>Lewis Tunstall</strong></a> 是 Hugging Face 的机器学习工程师，专注于开发开源工具并使更广泛的社区可以使用它们。他也是即将出版的一本书 <a href="https://www.oreilly.com/library/view/natural-language-processing/9781098136789/" rel="nofollow">O’Reilly book on Transformers</a> 的作者之一。</p> <p data-svelte-h="svelte-jyjyoh"><a href="https://huggingface.co/lvwerra" rel="nofollow"><strong>Leandro von Werra</strong></a> 是 Hugging Face 开源团队的机器学习工程师，也是即将出版的一本书 <a href="https://www.oreilly.com/library/view/natural-language-processing/9781098136789/" rel="nofollow">O’Reilly book on Transformers</a> 的作者之一。他拥有多年的行业经验，并在整个机器学习技术栈上进行了工作。</p> <h2 class="relative group"><a id="faq" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#faq"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>FAQ</span></h2> <p data-svelte-h="svelte-l20kb1">这里有一些经常被提到的问题：</p> <ul data-svelte-h="svelte-1x9o2l0"><li><p><strong>参加本课程是否会获得认证？</strong> | |
| 目前我们还没有为这门课程提供认证。然而，我们正在为 Hugging Face 生态系统制定认证计划——敬请期待！</p></li> <li><p><strong>我应该在这门课程上花多少时间？</strong> | |
| 本课程的每一章都设计为在 1 周内完成，每周大约需要 6-8 小时的学习时间。但是，但你可以根据自己的需要随意安排学习时间。</p></li> <li><p><strong>如果我有问题，我可以在哪里提问？</strong> | |
| 如果你对课程的任何部分有疑问，只需单击页面顶部的“<em>提问</em>”横幅，系统就会自动跳转到 [Hugging Face 论坛](https:// discuss.huggingface.co/) ：</p></li></ul> <img src="https://huggingface.co/datasets/huggingface-course/documentation-images/resolve/main/en/chapter1/forum-button.png" alt="Hugging Face论坛链接" width=" 75%"> <p data-svelte-h="svelte-1uvwh1o">请注意，如果你想在完成课程后进行更多练习，论坛上还提供了 <a href="https://discuss.huggingface.co/c/course/course-event/25" rel="nofollow">项目灵感</a> 列表，如果你希望在完成课程后进行更多实践，可以参考这些想法。</p> <ul data-svelte-h="svelte-qdg7ap"><li><strong>我在哪里可以获得课程的代码？</strong> | |
| 对于每个部分，单击页面顶部的横幅可以在 Google Colab 或 Amazon SageMaker Studio Lab 中运行代码：</li></ul> <img src="https://huggingface.co/datasets/huggingface-course/documentation-images/resolve/main/en/chapter1/notebook-buttons.png" alt="Hugging Face课程Notebook 链接" width="75%"> <p data-svelte-h="svelte-1p8r52r">包含课程所有代码的 Jupyter Notebook 托管在 <a href="https://github.com/huggingface/notebooks" rel="nofollow"><code>huggingface/notebooks</code></a> 仓库中。如果你希望在本地生成它们，请查看 GitHub 上 <a href="https://github.com/huggingface/course#-jupyter-notebooks" rel="nofollow"><code>course</code></a> 仓库中的说明。</p> <ul data-svelte-h="svelte-1dc1zyc"><li><p><strong>我如何为课程做出贡献？</strong> | |
| 有很多方法可以为课程做出贡献！如果你发现拼写错误或错误，请在 <a href="https://github.com/huggingface/course" rel="nofollow"><code>course</code></a> 仓库中提出问题。如果你想帮助将课程翻译成你的母语，请在 <a href="https://github.com/huggingface/course#translating-the-course-into-your-language" rel="nofollow">此处</a> 查看说明。</p></li> <li><p><strong>翻译的时候有没有术语表</strong> | |
| 每个翻译都有一个词汇表和“TRANSLATING.txt”文件，其中详细说明了为机器学习术语等所做的选择。你可以在 <a href="https://github.com/huggingface/course/blob/main/chapters/de/TRANSLATING.txt" rel="nofollow">此处</a> 找到德语的示例。</p></li></ul> <ul data-svelte-h="svelte-1y5bzb7"><li><strong>我可以使用这门课程再次进行创作吗？</strong> | |
| 当然！该课程是根据宽松的 <a href="https://www.apache.org/licenses/LICENSE-2.0.html" rel="nofollow">Apache 2 许可证</a> 发布的。这意味着你必须按照诚信的原则，提供许可证的链接，并指出是否进行了更改。你可以以任何合理的方式这样做，但不能以任何表明许可方认可你或你的使用的方式。如果你想引用该课程，请使用以下 BibTeX：</li></ul> <div class="code-block relative "><div class="absolute top-2.5 right-4"><button class="inline-flex items-center relative text-sm focus:text-green-500 cursor-pointer focus:outline-none transition duration-200 ease-in-out opacity-0 mx-0.5 text-gray-600 " title="code excerpt" type="button"><svg class="" xmlns="http://www.w3.org/2000/svg" aria-hidden="true" fill="currentColor" focusable="false" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 32 32"><path d="M28,10V28H10V10H28m0-2H10a2,2,0,0,0-2,2V28a2,2,0,0,0,2,2H28a2,2,0,0,0,2-2V10a2,2,0,0,0-2-2Z" transform="translate(0)"></path><path d="M4,18H2V4A2,2,0,0,1,4,2H18V4H4Z" transform="translate(0)"></path><rect fill="none" width="32" height="32"></rect></svg> <div class="absolute pointer-events-none transition-opacity bg-black text-white py-1 px-2 leading-tight rounded font-normal shadow left-1/2 top-full transform -translate-x-1/2 translate-y-2 opacity-0"><div class="absolute bottom-full left-1/2 transform -translate-x-1/2 w-0 h-0 border-black border-4 border-t-0" style="border-left-color: transparent; border-right-color: transparent; "></div> Copied</div></button></div> <pre class=""><!-- HTML_TAG_START --><span class="language-xml">@misc</span><span class="hljs-template-variable">{huggingfacecourse, | |
| author = {Hugging Face}</span><span class="language-xml">, | |
| title = </span><span class="hljs-template-variable">{The Hugging Face Course, 2022}</span><span class="language-xml">, | |
| howpublished = "\url</span><span class="hljs-template-variable">{https://huggingface.co/course}</span><span class="language-xml">", | |
| year = </span><span class="hljs-template-variable">{2022}</span><span class="language-xml">, | |
| note = "[Online; accessed <span class="hljs-tag"><<span class="hljs-name">today</span>></span>]" | |
| }</span><!-- HTML_TAG_END --></pre></div> <h2 class="relative group"><a id="让我们开始吧！" class="header-link block pr-1.5 text-lg no-hover:hidden with-hover:absolute with-hover:p-1.5 with-hover:opacity-0 with-hover:group-hover:opacity-100 with-hover:right-full" href="#让我们开始吧！"><span><svg class="" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" aria-hidden="true" role="img" width="1em" height="1em" preserveAspectRatio="xMidYMid meet" viewBox="0 0 256 256"><path d="M167.594 88.393a8.001 8.001 0 0 1 0 11.314l-67.882 67.882a8 8 0 1 1-11.314-11.315l67.882-67.881a8.003 8.003 0 0 1 11.314 0zm-28.287 84.86l-28.284 28.284a40 40 0 0 1-56.567-56.567l28.284-28.284a8 8 0 0 0-11.315-11.315l-28.284 28.284a56 56 0 0 0 79.196 79.197l28.285-28.285a8 8 0 1 0-11.315-11.314zM212.852 43.14a56.002 56.002 0 0 0-79.196 0l-28.284 28.284a8 8 0 1 0 11.314 11.314l28.284-28.284a40 40 0 0 1 56.568 56.567l-28.285 28.285a8 8 0 0 0 11.315 11.314l28.284-28.284a56.065 56.065 0 0 0 0-79.196z" fill="currentColor"></path></svg></span></a> <span>让我们开始吧！</span></h2> <p data-svelte-h="svelte-171vnpf">你准备好了吗？在本章中，你将学习：</p> <ul data-svelte-h="svelte-pkhygh"><li>如何使用 <code>pipeline()</code> 函数解决文本生成、分类等 NLP 任务</li> <li>关于 Transformer 架构</li> <li>如何区分编码器、解码器和编码器-解码器架构和用例</li></ul> <a class="!text-gray-400 !no-underline text-sm flex items-center not-prose mt-4" href="https://github.com/huggingface/course/blob/main/chapters/zh-CN/chapter1/1.mdx" target="_blank"><span data-svelte-h="svelte-1kd6by1"><</span> <span data-svelte-h="svelte-x0xyl0">></span> <span data-svelte-h="svelte-1dajgef"><span class="underline ml-1.5">Update</span> on GitHub</span></a> <p></p> | |
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