diff --git a/README.md b/README.md index cab0d80..b6cab8f 100644 --- a/README.md +++ b/README.md @@ -1,23 +1,19 @@ + +> [!NOTE] +> 本文档由 WeHub 基于上游 README 翻译整理，属于社区翻译，非官方中文文档。 +> [English](./README.en.md) · [原始项目](https://github.com/explosion/spaCy) · [上游 README](https://github.com/explosion/spaCy/blob/HEAD/README.md) +> 原作者、版权与许可证归属以原始项目及本仓库 LICENSE 文件为准。 + -# spaCy: Industrial-strength NLP +# spaCy：工业级 NLP -spaCy is a library for **advanced Natural Language Processing** in Python and -Cython. It's built on the very latest research, and was designed from day one to -be used in real products. +spaCy 是一个用于 Python 和 Cython 的**高级自然语言处理（Natural Language Processing）**库。它基于最前沿的研究成果，从诞生之初就面向真实产品场景而设计。 -spaCy comes with [pretrained pipelines](https://spacy.io/models) and currently -supports tokenization and training for **70+ languages**. It features -state-of-the-art speed and **neural network models** for tagging, parsing, -**named entity recognition**, **text classification** and more, multi-task -learning with pretrained **transformers** like BERT, as well as a -production-ready [**training system**](https://spacy.io/usage/training) and easy -model packaging, deployment and workflow management. spaCy is commercial -open-source software, released under the -[MIT license](https://github.com/explosion/spaCy/blob/master/LICENSE). +spaCy 提供[预训练流水线（pretrained pipelines）](https://spacy.io/models)，目前支持 **70+** 种语言的词元化（tokenization）与训练。它在词性标注、句法分析、**命名实体识别（named entity recognition）**、**文本分类（text classification）**等任务上具备顶尖速度与**神经网络模型**，支持基于 BERT 等预训练 **Transformer** 的多任务学习，还提供生产就绪的[**训练系统（training system）**](https://spacy.io/usage/training)，以及便捷的模型打包、部署与工作流管理。spaCy 是商业开源软件，采用 [MIT 许可证（MIT license）](https://github.com/explosion/spaCy/blob/master/LICENSE). -💫 **Version 3.8 out now!** -[Check out the release notes here.](https://github.com/explosion/spaCy/releases) +💫 **3.8 版本现已发布！** +[在此查看发行说明。](https://github.com/explosion/spaCy/releases) [![tests](https://github.com/explosion/spaCy/actions/workflows/tests.yml/badge.svg)](https://github.com/explosion/spaCy/actions/workflows/tests.yml) [![Current Release Version](https://img.shields.io/github/release/explosion/spacy.svg?style=flat-square&logo=github)](https://github.com/explosion/spaCy/releases) @@ -29,30 +25,30 @@ open-source software, released under the [![PyPi downloads](https://static.pepy.tech/personalized-badge/spacy?period=total&units=international_system&left_color=grey&right_color=orange&left_text=pip%20downloads)](https://pypi.org/project/spacy/) [![Conda downloads](https://img.shields.io/conda/dn/conda-forge/spacy?label=conda%20downloads)](https://anaconda.org/conda-forge/spacy) -## 📖 Documentation +## 📖 文档 -| Documentation | | +| 文档 | | | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| ⭐️ **[spaCy 101]** | New to spaCy? Here's everything you need to know! | -| 📚 **[Usage Guides]** | How to use spaCy and its features. | -| 🚀 **[New in v3.0]** | New features, backwards incompatibilities and migration guide. | -| 🪐 **[Project Templates]** | End-to-end workflows you can clone, modify and run. | -| 🎛 **[API Reference]** | The detailed reference for spaCy's API. | -| ⏩ **[GPU Processing]** | Use spaCy with CUDA-compatible GPU processing. | -| 📦 **[Models]** | Download trained pipelines for spaCy. | -| 🦙 **[Large Language Models]** | Integrate LLMs into spaCy pipelines. | -| 🌌 **[Universe]** | Plugins, extensions, demos and books from the spaCy ecosystem. | -| ⚙️ **[spaCy VS Code Extension]** | Additional tooling and features for working with spaCy's config files. | -| 👩‍🏫 **[Online Course]** | Learn spaCy in this free and interactive online course. | -| 📰 **[Blog]** | Read about current spaCy and Prodigy development, releases, talks and more from Explosion. | -| 📺 **[Videos]** | Our YouTube channel with video tutorials, talks and more. | -| 🔴 **[Live Stream]** | Join Matt as he works on spaCy and chat about NLP. | -| 🛠 **[Changelog]** | Changes and version history. | -| 💝 **[Contribute]** | How to contribute to the spaCy project and code base. | -| 👕 **[Swag]** | Support us and our work with unique, custom-designed swag! | -| Tailored Solutions | Custom NLP consulting, implementation and strategic advice by spaCy’s core development team. Streamlined, production-ready, predictable and maintainable. Send us an email or take our 5-minute questionnaire, and well'be in touch! **[Learn more →](https://explosion.ai/tailored-solutions)** | +| ⭐️ **[spaCy 101]** | 初次接触 spaCy？这里有你需要了解的一切！ | +| 📚 **[Usage Guides]** | 如何使用 spaCy 及其功能。 | +| 🚀 **[New in v3.0]** | 新功能、向后不兼容变更与迁移指南。 | +| 🪐 **[Project Templates]** | 可克隆、修改并运行的端到端工作流。 | +| 🎛 **[API Reference]** | spaCy API 的详细参考文档。 | +| ⏩ **[GPU Processing]** | 在兼容 CUDA 的 GPU 上运行 spaCy。 | +| 📦 **[Models]** | 下载 spaCy 的训练流水线。 | +| 🦙 **[Large Language Models]** | 将大语言模型（LLM）集成到 spaCy 流水线中。 | +| 🌌 **[Universe]** | spaCy 生态中的插件、扩展、演示与书籍。 | +| ⚙️ **[spaCy VS Code Extension]** | 用于处理 spaCy 配置文件的额外工具与功能。 | +| 👩‍🏫 **[Online Course]** | 在这门免费互动在线课程中学习 spaCy。 | +| 📰 **[Blog]** | 阅读 Explosion 关于 spaCy 与 Prodigy 的最新开发动态、版本发布、演讲等内容。 | +| 📺 **[Videos]** | 我们的 YouTube 频道，提供视频教程、演讲等内容。 | +| 🔴 **[Live Stream]** | 与 Matt 一起直播开发 spaCy，畅聊 NLP。 | +| 🛠 **[Changelog]** | 变更与版本历史。 | +| 💝 **[Contribute]** | 如何为 spaCy 项目与代码库做贡献。 | +| 👕 **[Swag]** | 购买独特定制周边，支持我们及我们的工作！ | +| 定制解决方案 | 由 spaCy 核心开发团队提供的定制 NLP 咨询、实施与战略建议。精简、生产就绪、可预测且易于维护。给我们发邮件或填写 5 分钟问卷，我们会尽快与您联系！**[了解更多 →](https://explosion.ai/tailored-solutions)** | -[spacy 101]: https://spacy.io/usage/spacy-101 +[spaCy 101]: https://spacy.io/usage/spacy-101 [new in v3.0]: https://spacy.io/usage/v3 [usage guides]: https://spacy.io/usage/ [api reference]: https://spacy.io/api/ @@ -70,79 +66,73 @@ open-source software, released under the [contribute]: https://github.com/explosion/spaCy/blob/master/CONTRIBUTING.md [swag]: https://explosion.ai/merch -## 💬 Where to ask questions +## 💬 在哪里提问 -The spaCy project is maintained by the [spaCy team](https://explosion.ai/about). -Please understand that we won't be able to provide individual support via email. -We also believe that help is much more valuable if it's shared publicly, so that -more people can benefit from it. +spaCy 项目由 [spaCy 团队](https://explosion.ai/about). +维护。请注意，我们无法通过电子邮件提供一对一支持。 +我们也认为，公开分享的帮助更有价值，这样更多人可以从中受益。 -| Type | Platforms | +| 类型 | 平台 | | ------------------------------- | --------------------------------------- | -| 🚨 **Bug Reports** | [GitHub Issue Tracker] | -| 🎁 **Feature Requests & Ideas** | [GitHub Discussions] · [Live Stream] | -| 👩‍💻 **Usage Questions** | [GitHub Discussions] · [Stack Overflow] | -| 🗯 **General Discussion** | [GitHub Discussions] · [Live Stream] | +| 🚨 **缺陷报告** | [GitHub Issue Tracker] | +| 🎁 **功能请求与想法** | [GitHub Discussions] · [Live Stream] | +| 👩‍💻 **使用问题** | [GitHub Discussions] · [Stack Overflow] | +| 🗯 **一般讨论** | [GitHub Discussions] · [Live Stream] | [github issue tracker]: https://github.com/explosion/spaCy/issues [github discussions]: https://github.com/explosion/spaCy/discussions [stack overflow]: https://stackoverflow.com/questions/tagged/spacy [live stream]: https://www.youtube.com/playlist?list=PLBmcuObd5An5_iAxNYLJa_xWmNzsYce8c -## Features +## 特性 -- Support for **70+ languages** -- **Trained pipelines** for different languages and tasks -- Multi-task learning with pretrained **transformers** like BERT -- Support for pretrained **word vectors** and embeddings -- State-of-the-art speed -- Production-ready **training system** -- Linguistically-motivated **tokenization** -- Components for named **entity recognition**, part-of-speech-tagging, - dependency parsing, sentence segmentation, **text classification**, - lemmatization, morphological analysis, entity linking and more -- Easily extensible with **custom components** and attributes -- Support for custom models in **PyTorch**, **TensorFlow** and other frameworks -- Built in **visualizers** for syntax and NER -- Easy **model packaging**, deployment and workflow management -- Robust, rigorously evaluated accuracy +- 支持 **70+ 种语言** +- 适用于不同语言和任务的 **训练流水线（pipeline）** +- 多任务学习，使用 BERT 等预训练 **transformer** +- 支持预训练 **词向量（word vectors）** 和嵌入（embeddings） +- 业界领先的运行速度 +- 可用于生产的 **训练系统** +- 基于语言学动机的 **分词（tokenization）** +- 命名 **实体识别（NER）**、词性标注、依存句法分析、句子分割、**文本分类**、词形还原、形态学分析、实体链接等组件 +- 可通过 **自定义组件** 和属性轻松扩展 +- 支持在 **PyTorch**、**TensorFlow** 及其他框架中使用自定义模型 +- 内置句法和 NER 的 **可视化工具（visualizer）** +- 便捷的 **模型打包**、部署与工作流管理 +- 稳健、经过严格评估的准确度 -📖 **For more details, see the -[facts, figures and benchmarks](https://spacy.io/usage/facts-figures).** +📖 **更多详情请参阅 +[事实、数据与基准测试](https://spacy.io/usage/facts-figures).** -## ⏳ Install spaCy +## ⏳ 安装 spaCy -For detailed installation instructions, see the -[documentation](https://spacy.io/usage). +详细安装说明请参阅 +[文档](https://spacy.io/usage). -- **Operating system**: macOS / OS X · Linux · Windows (Cygwin, MinGW, Visual - Studio) -- **Python version**: Python >=3.7, <3.13 (only 64 bit) -- **Package managers**: [pip] · [conda] (via `conda-forge`) +- **操作系统**：macOS / OS X · Linux · Windows（Cygwin、MinGW、Visual + Studio） +- **Python 版本**：Python >=3.7，<3.13（仅 64 位） +- **包管理器**：[pip] · [conda]（通过 `conda-forge`） [pip]: https://pypi.org/project/spacy/ [conda]: https://anaconda.org/conda-forge/spacy ### pip -Using pip, spaCy releases are available as source packages and binary wheels. -Before you install spaCy and its dependencies, make sure that your `pip`, -`setuptools` and `wheel` are up to date. +使用 pip 时，spaCy 发布包提供源码包和二进制 wheel 包。 +在安装 spaCy 及其依赖之前，请确保你的 `pip`、 +`setuptools` 和 `wheel` 已是最新版本。 ```bash pip install -U pip setuptools wheel pip install spacy ``` -To install additional data tables for lemmatization and normalization you can -run `pip install spacy[lookups]` or install -[`spacy-lookups-data`](https://github.com/explosion/spacy-lookups-data) -separately. The lookups package is needed to create blank models with -lemmatization data, and to lemmatize in languages that don't yet come with -pretrained models and aren't powered by third-party libraries. +要安装用于词形还原和规范化的额外数据表，可以 +运行 `pip install spacy[lookups]`，或单独安装 +[`spacy-lookups-data`](https://github.com/explosion/spacy-lookups-data)。 +lookups 包用于创建带有词形还原数据的空白模型，以及在尚未提供预训练模型、且不依赖第三方库的语言中进行词形还原。 -When using pip it is generally recommended to install packages in a virtual -environment to avoid modifying system state: +使用 pip 时，通常建议在虚拟环境中安装软件包，以避免修改系统状态： ```bash python -m venv .env @@ -153,45 +143,38 @@ pip install spacy ### conda -You can also install spaCy from `conda` via the `conda-forge` channel. For the -feedstock including the build recipe and configuration, check out -[this repository](https://github.com/conda-forge/spacy-feedstock). +你也可以通过 `conda-forge` 频道从 `conda` 安装 spaCy。有关包含构建配方和配置的 feedstock，请参阅 +[此仓库](https://github.com/conda-forge/spacy-feedstock). ```bash conda install -c conda-forge spacy ``` -### Updating spaCy +### 更新 spaCy -Some updates to spaCy may require downloading new statistical models. If you're -running spaCy v2.0 or higher, you can use the `validate` command to check if -your installed models are compatible and if not, print details on how to update -them: +spaCy 的某些更新可能需要下载新的统计模型。如果你运行的是 spaCy v2.0 或更高版本，可以使用 `validate` 命令检查已安装模型是否兼容；若不兼容，会输出如何更新它们的详细信息： ```bash pip install -U spacy python -m spacy validate ``` -If you've trained your own models, keep in mind that your training and runtime -inputs must match. After updating spaCy, we recommend **retraining your models** -with the new version. +如果你训练了自己的模型，请注意训练时与运行时的输入必须一致。更新 spaCy 后，我们建议使用新版本 **重新训练你的模型**。 -📖 **For details on upgrading from spaCy 2.x to spaCy 3.x, see the -[migration guide](https://spacy.io/usage/v3#migrating).** +📖 **有关从 spaCy 2.x 升级到 spaCy 3.x 的详情，请参阅 +[迁移指南](https://spacy.io/usage/v3#migrating).** -## 📦 Download model packages +## 📦 下载模型包 -Trained pipelines for spaCy can be installed as **Python packages**. This means -that they're a component of your application, just like any other module. Models -can be installed using spaCy's [`download`](https://spacy.io/api/cli#download) -command, or manually by pointing pip to a path or URL. +spaCy 的训练流水线可作为 **Python 软件包** 安装。这意味着 +它们是你应用程序的组成部分，就像任何其他模块一样。可以使用 spaCy 的 [`download`](https://spacy.io/api/cli#download) +命令安装模型，也可以通过让 pip 指向路径或 URL 手动安装。 -| Documentation | | +| 文档 | | | -------------------------- | ---------------------------------------------------------------- | -| **[Available Pipelines]** | Detailed pipeline descriptions, accuracy figures and benchmarks. | -| **[Models Documentation]** | Detailed usage and installation instructions. | -| **[Training]** | How to train your own pipelines on your data. | +| **[可用流水线]** | 详细的流水线说明、准确度数据与基准测试。 | +| **[模型文档]** | 详细的使用与安装说明。 | +| **[训练]** | 如何在自己的数据上训练自定义流水线。 | [available pipelines]: https://spacy.io/models [models documentation]: https://spacy.io/usage/models @@ -207,10 +190,10 @@ pip install /Users/you/en_core_web_sm-3.0.0-py3-none-any.whl pip install https://github.com/explosion/spacy-models/releases/download/en_core_web_sm-3.0.0/en_core_web_sm-3.0.0.tar.gz ``` -### Loading and using models +### 加载和使用模型 -To load a model, use [`spacy.load()`](https://spacy.io/api/top-level#spacy.load) -with the model name or a path to the model data directory. +要加载模型，请使用 [`spacy.load()`](https://spacy.io/api/top-level#spacy.load) +，并传入模型名称或模型数据目录的路径。 ```python import spacy @@ -218,8 +201,8 @@ nlp = spacy.load("en_core_web_sm") doc = nlp("This is a sentence.") ``` -You can also `import` a model directly via its full name and then call its -`load()` method with no arguments. +你也可以通过模型的完整名称直接 `import`，然后无参调用其 +`load()` 方法。 ```python import spacy @@ -229,31 +212,28 @@ nlp = en_core_web_sm.load() doc = nlp("This is a sentence.") ``` -📖 **For more info and examples, check out the -[models documentation](https://spacy.io/docs/usage/models).** +📖 **更多信息和示例，请参阅 +[模型文档](https://spacy.io/docs/usage/models).** -## ⚒ Compile from source +## ⚒ 从源码编译 -The other way to install spaCy is to clone its -[GitHub repository](https://github.com/explosion/spaCy) and build it from -source. That is the common way if you want to make changes to the code base. -You'll need to make sure that you have a development environment consisting of a -Python distribution including header files, a compiler, +安装 spaCy 的另一种方式是克隆其 +[GitHub 仓库](https://github.com/explosion/spaCy)，并从源码构建。 +如果你想修改代码库，这通常是常用的方式。 +你需要确保已具备开发环境，包括带头文件的 Python 发行版、编译器、 [pip](https://pip.pypa.io/en/latest/installing/), -[virtualenv](https://virtualenv.pypa.io/en/latest/) and -[git](https://git-scm.com) installed. The compiler part is the trickiest. How to -do that depends on your system. +[virtualenv](https://virtualenv.pypa.io/en/latest/) 和 +[git](https://git-scm.com) 已安装。编译器部分最为棘手，具体做法取决于你的系统。 -| Platform | | +| 平台 | | | ----------- | ------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- | -| **Ubuntu** | Install system-level dependencies via `apt-get`: `sudo apt-get install build-essential python-dev git` . | -| **Mac** | Install a recent version of [XCode](https://developer.apple.com/xcode/), including the so-called "Command Line Tools". macOS and OS X ship with Python and git preinstalled. | -| **Windows** | Install a version of the [Visual C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) or [Visual Studio Express](https://visualstudio.microsoft.com/vs/express/) that matches the version that was used to compile your Python interpreter. | +| **Ubuntu** | 通过 `apt-get` 安装系统级依赖：`sudo apt-get install build-essential python-dev git`。 | +| **Mac** | 安装最新版 [XCode](https://developer.apple.com/xcode/),，其中包含所谓的「Command Line Tools」。macOS 和 OS X 预装了 Python 和 git。 | +| **Windows** | 安装与你的 Python 解释器编译所用版本相匹配的 [Visual C++ Build Tools](https://visualstudio.microsoft.com/visual-cpp-build-tools/) 或 [Visual Studio Express](https://visualstudio.microsoft.com/vs/express/)。 | -For more details and instructions, see the documentation on -[compiling spaCy from source](https://spacy.io/usage#source) and the -[quickstart widget](https://spacy.io/usage#section-quickstart) to get the right -commands for your platform and Python version. +如需更多详情和操作说明，请参阅 +[从源码编译 spaCy](https://spacy.io/usage#source) 以及 +[快速入门 widget](https://spacy.io/usage#section-quickstart)，以获取适用于你的平台与 Python 版本的正确命令。 ```bash git clone https://github.com/explosion/spaCy @@ -269,22 +249,17 @@ pip install -r requirements.txt pip install --no-build-isolation --editable . ``` -To install with extras: +安装 extras 扩展： ```bash pip install --no-build-isolation --editable .[lookups,cuda102] ``` -## 🚦 Run tests +## 🚦 运行测试 -spaCy comes with an [extensive test suite](spacy/tests). In order to run the -tests, you'll usually want to clone the repository and build spaCy from source. -This will also install the required development dependencies and test utilities -defined in the [`requirements.txt`](requirements.txt). +spaCy 附带[完善的测试套件](spacy/tests)。要运行测试，你通常需要克隆仓库并从源码构建 spaCy。这也会安装 [`requirements.txt`](requirements.txt) 中定义的必要开发依赖与测试工具。 -Alternatively, you can run `pytest` on the tests from within the installed -`spacy` package. Don't forget to also install the test utilities via spaCy's -[`requirements.txt`](requirements.txt): +或者，你也可以在已安装的 `spacy` 包内对测试运行 `pytest`。别忘了通过 spaCy 的 [`requirements.txt`](requirements.txt) 安装测试工具： ```bash pip install -r requirements.txt