chore(doc): refine some docs

star-whale · Mar 23, 2023 · 74540c9 · 74540c9
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diff --git a/docs/docs/concepts/names.md b/docs/docs/concepts/names.md
@@ -4,14 +4,14 @@ title: Names in Starwhale
 
 Names mean project names, model names, dataset names, runtime names, and tag names.
 
-# 1. Names Limitation
+## 1. Names Limitation
 
 - Names are case-insensitive.
 - A name MUST only consist of letters `A-Z a-z`, digits `0-9`, the hyphen character `-`, the dot character `.`, and the underscore character `_`.
 - A name should always start with a letter or the `_` character.
 - The maximum length of a name is 80.
 
-# 2. Names uniqueness requirement
+## 2. Names uniqueness requirement
 
 The resource name should be a unique string within its owner. For example, the project name should be unique in the owner instance, and the model name should be unique in the owner project.
 

diff --git a/docs/docs/dataset/index.md b/docs/docs/dataset/index.md
@@ -20,4 +20,4 @@ To create/update a dataset, see [Create/update a Starwhale dataset](creation) fo
 
 Starwhale datasets are versioned. This feature helps you to keep track of all modifications of a dataset. And you can always run your model evaluation by specifying a specific dataset version, regardless of any future changes to the dataset. In this way, model evaluations in Starwhale are stable and comparatable. For more information about versioning in Starwhale, see [Resource versioning in Starwhale](../common/versioning).
 
-The Starwhale Command Line Interface (SWCLI) provides dataset related commands. For more information, see [SWCLI reference guide](../references/swcli/dataset).
+The Starwhale Client (SWCLI) provides dataset related commands. For more information, see [SWCLI reference guide](../references/swcli/dataset).
diff --git a/docs/docs/getting-started/cloud.md b/docs/docs/getting-started/cloud.md
@@ -4,38 +4,38 @@ title: Getting started with Starwhale Cloud
 
 Starwhale Cloud is hosted on [AWS](https://cloud.starwhale.ai) and [Aliyun](https://cloud.starwhale.cn). These are two independent instances. Accounts and data are not shared. You can choose anyone you like.
 
-You need to install the [Starwhale Command Line Interface (SWCLI)](../swcli) at first.
+You need to install the [Starwhale Client (SWCLI)](../swcli) at first.
 
-# 1. Sign Up for Starwhale Cloud and create your first project
+## 1. Sign Up for Starwhale Cloud and create your first project
 
 You can either directly log in with your GitHub or Google account or sign up for an account. You will be asked for an account name if you log in with your GitHub or Google account. For more information, see the [Starwhale Cloud user guide - Create your account](../starwhale-cloud/index)
 
 Then you can create a new project. In this tutorial, we will use the name `demo` for the project name.
 
-# 2. Build the dataset, model, and runtime on your local machine
+## 2. Build the dataset, model, and runtime on your local machine
 
 Follow step 1 to step 4 in [Getting started with Starwhale Standalone](standalone) to create:
 
 - a Starwhale model named mnist
 - a Starwhale dataset named mnist
 - a Starwhale runtime named pytorch
 
-# 3. Login to the cloud instance
+## 3. Login to the cloud instance
 
 ```bash
 swcli instance login --username <your account name> --password <your password> --alias swcloud https://cloud.starwhale.ai
 # replace the URL with https://cloud.starwhale.cn if you choose to use Starwhale Cloud CN
 ```
 
-# 4. Copy the dataset, model, and runtime to the cloud instance
+## 4. Copy the dataset, model, and runtime to the cloud instance
 
 ```bash
 swcli model copy mnist/version/latest swcloud/project/demo
 swcli dataset copy mnist/version/latest swcloud/project/demo
 swcli runtime copy pytorch/version/latest swcloud/project/demo
 ```
 
-# 5.Run an evaluation with the web UI
+## 5.Run an evaluation with the web UI
 
 ![console-create-job.gif](../img/console-create-job.gif)
 

diff --git a/docs/docs/getting-started/index.md b/docs/docs/getting-started/index.md
@@ -2,7 +2,7 @@
 title: Getting started
 ---
 
-First, you need to install the [Starwhale Command Line Interface (SWCLI)](../swcli), which can be done by running the following command
+First, you need to install the [Starwhale Client (SWCLI)](../swcli), which can be done by running the following command
 
 ```bash
 python3 -m pip install starwhale

diff --git a/docs/docs/getting-started/server.md b/docs/docs/getting-started/server.md
@@ -2,29 +2,29 @@
 title: Getting started with Starwhale Server
 ---
 
-# 1. Install Starwhale Server
+## 1. Install Starwhale Server
 
 To install Starwhale Server, see the [installation guide]
 
-# 2. Create your first project
+## 2. Create your first project
 
-## 2.1 Login to the server
+### 2.1 Login to the server
 
 Open your browser and enter your server's URL in the address bar. Login with your username(starwhale) and password(abcd1234).
 
 ![console-artifacts.gif](../img/console-artifacts.gif)
 
-## 2.2 Create a new project
+### 2.2 Create a new project
 
-# 3. Build the dataset, model, and runtime on your local machine
+## 3. Build the dataset, model, and runtime on your local machine
 
 Follow step 1 to step 4 in [Getting started with Starwhale Standalone](standalone) to create:
 
 - a Starwhale model named mnist
 - a Starwhale dataset named mnist
 - a Starwhale runtime named pytorch
 
-# 4. Copy the dataset, the model, and the runtime to the server
+## 4. Copy the dataset, the model, and the runtime to the server
 
 ```bash
 swcli instance login --username <your username> --password <your password> --alias server <Your Server URL>
@@ -33,7 +33,7 @@ swcli dataset copy mnist/version/latest server/project/demo
 swcli runtime copy pytorch/version/latest server/project/demo
 ```
 
-# 3. Use the Web UI to run an evaluation
+## 5. Use the Web UI to run an evaluation
 
 Navigate to the "demo" project in your browser and create a new one.
 

diff --git a/docs/docs/getting-started/standalone.md b/docs/docs/getting-started/standalone.md
@@ -2,9 +2,9 @@
 title: Getting started with Starwhale Standalone
 ---
 
-When the [Starwhale Command Line Interface (SWCLI)](../swcli) is installed, you are ready to use Starwhale Standalone.
+When the [Starwhale Client (SWCLI)](../swcli) is installed, you are ready to use Starwhale Standalone.
 
-# 1. Downloading Examples
+## 1. Downloading Examples
 
 Download Starwhale examples by cloning the Starwhale project via:
 
@@ -17,7 +17,7 @@ We will use MNIST with PyTorch to start your Starwhale journey. The following st
 
 ![Core Workflow](../img/standalone-core-workflow.gif)
 
-# 2. Building a Pytorch Runtime
+## 2. Building a Pytorch Runtime
 
 Runtime example codes are in the `example/runtime/pytorch` directory.
 
@@ -34,7 +34,7 @@ Runtime example codes are in the `example/runtime/pytorch` directory.
   swcli runtime info pytorch/version/latest
   ```
 
-# 3. Building a Model
+## 3. Building a Model
 
 Model example codes are in the `example/mnist` directory.
 
@@ -61,7 +61,7 @@ Model example codes are in the `example/mnist` directory.
   swcli model info mnist/version/latest
   ```
 
-# 4. Building a Dataset
+## 4. Building a Dataset
 
 Dataset example codes are in the `example/mnist` directory.
 
@@ -88,7 +88,7 @@ Dataset example codes are in the `example/mnist` directory.
   swcli dataset info mnist/version/latest
   ```
 
-# 5. Running an Evaluation Job
+## 5. Running an Evaluation Job
 
 - Create an evaluation job
 

diff --git a/docs/docs/swcli/index.md b/docs/docs/swcli/index.md
@@ -1,8 +1,8 @@
 ---
-title: Starwhale Command Line Interface (SWCLI) User Guide
+title: Starwhale Client (SWCLI) User Guide
 ---
 
-The Starwhale Command Line Interface (SWCLI) is a command-line tool that enables you to interact with Starwhale instances. You can use SWCLI to complete almost all tasks in Starwhale.
+The Starwhale Client (SWCLI) is a command-line tool that enables you to interact with Starwhale instances. You can use SWCLI to complete almost all tasks in Starwhale.
 
 SWCLI is written in pure python3 (require Python 3.7+), so that it can be easily installed by the `pip` command.
 

diff --git a/docs/docs/swcli/installation.md b/docs/docs/swcli/installation.md
@@ -6,7 +6,7 @@ Installing SWCLI in your system's global Python environment may cause a python d
 
 Here are some installation tips that can help you get a cleaner, unambiguous, no dependency conflicts `swcli` python environment.
 
-# 1. Prerequisites
+## 1. Prerequisites
 
 * Python 3.7+
 * Linux or macOS
@@ -29,9 +29,9 @@ SWCLI works on macOS. If you run into issues with the default system Python3 on
 brew install python3
 ```
 
-# 2. Install SWCLI
+## 2. Install SWCLI
 
-## Install with venv
+### Install with venv
 
 ```bash
 python3 -m venv ~/.cache/venv/starwhale
@@ -44,7 +44,7 @@ sudo rm -rf /usr/local/bin/swcli
 sudo ln -s `which swcli` /usr/local/bin/
 ```
 
-## Install with conda
+### Install with conda
 
 ```bash
 conda create --name starwhale --yes  python=3.9
@@ -59,7 +59,7 @@ sudo ln -s `which swcli` /usr/local/bin/
 
 👏 Now, you can use `swcli` in the global environment.
 
-# 3. Update SWCLI
+## 3. Update SWCLI
 
 ```bash
 #for venv
@@ -69,7 +69,7 @@ python3 -m pip install --upgrade starwhale
 conda run -n starwhale python3 -m pip install --upgrade starwhale
 ```
 
-# 4. Uninstall SWCLI
+## 4. Uninstall SWCLI
 
 ```bash
 python3 -m pip remove starwhale

diff --git a/docs/docs/what-is-starwhale.md b/docs/docs/what-is-starwhale.md
@@ -3,7 +3,7 @@ slug: /
 title: What is Starwhale
 ---
 
-# Overview
+## Overview
 
 Starwhale is an MLOps platform that make your model creation, evaluation and publication much eaiser. It aims to create a handy tool for data scientists and machine learning engineers.
 
@@ -16,14 +16,14 @@ Starwhale helps you
 
 Starwhale is designed to be an open platform. You can create your own plugins to meet your requirements.
 
-# Deployment options
+## Deployment options
 
-Each deployment of Starwhale is called an instance. All instances can be managed by the Starwhale Command Line Interface (SWCLI).
+Each deployment of Starwhale is called an instance. All instances can be managed by the Starwhale Client (SWCLI).
 
 You can start using Starwhale with one of the following instance types:
 
-* **Starwhale Standalone** - Rather than a running service, Starwhale Standalone is actually a repository that resides in your local file system. It is created and managed by the Starwhale Command Line Interface (SWCLI). You only need to install SWCLI to use it. Currently, each user on a single machine can have only ONE Starwhale Standalone instance. We recommend you use the Starwhale Standalone to build and test your datasets, runtime, and models before pushing them to Starwhale Server/Cloud instances.
-* **Starwhale Server** - Starwhale Server is a service deployed on your local server. Besides text-only results from the Starwhale Command Line Interface (SWCLI), Starwhale Server provides Web UI for you to manage your datasets and models, evaluate your models in your local Kubernetes cluster, and review the evaluation results.
+* **Starwhale Standalone** - Rather than a running service, Starwhale Standalone is actually a repository that resides in your local file system. It is created and managed by the Starwhale Client (SWCLI). You only need to install SWCLI to use it. Currently, each user on a single machine can have only ONE Starwhale Standalone instance. We recommend you use the Starwhale Standalone to build and test your datasets, runtime, and models before pushing them to Starwhale Server/Cloud instances.
+* **Starwhale Server** - Starwhale Server is a service deployed on your local server. Besides text-only results from the Starwhale Client (SWCLI), Starwhale Server provides Web UI for you to manage your datasets and models, evaluate your models in your local Kubernetes cluster, and review the evaluation results.
 * **Starwhale Cloud** - Starwhale Cloud is a managed service hosted on public clouds. By registering an account on <https://cloud.starwhale.ai> or <https://cloud.starwhale.cn>, you are ready to use Starwhale without needing to install, operate, and maintain your own instances. Starwhale Cloud also provides public resources for you to download, like datasets, runtimes, and models. Check the "starwhale/public" project on Starwhale Cloud for more details.
 
 When choosing which instance type to use, consider the following:

diff --git a/docs/i18n/zh/docusaurus-plugin-content-docs/current.json b/docs/i18n/zh/docusaurus-plugin-content-docs/current.json
@@ -12,7 +12,7 @@
         "message": "用户指南"
     },
     "sidebar.mainSidebar.category.Command Line Interface": {
-        "message": "Starwhale命令行"
+        "message": "Starwhale Client"
     },
     "sidebar.mainSidebar.category.Community": {
         "message": "社区"

diff --git a/docs/i18n/zh/docusaurus-plugin-content-docs/current/community/contribute.md b/docs/i18n/zh/docusaurus-plugin-content-docs/current/community/contribute.md
@@ -55,7 +55,7 @@ Starwhale社区使用[Github Issues](https://github.com/star-whale/starwhale/iss
 
 ## 4. Fork&Clone Starwhale仓库
 
-你需要fork Starwhale仓库代码并clone到本机，
+您需要fork Starwhale仓库代码并clone到本机，
 
 - Fork Starwhale仓库：[Fork Starwhale Github Repo](https://github.com/star-whale/starwhale/fork)，更多使用详情可参考：[Fork a repo](https://docs.github.com/en/get-started/quickstart/fork-a-repo)
 - 安装Git-LFS：[Git LFS](https://github.com/git-lfs/git-lfs/blob/main/INSTALLING.md#installing-packages)

diff --git a/docs/i18n/zh/docusaurus-plugin-content-docs/current/concepts/names.md b/docs/i18n/zh/docusaurus-plugin-content-docs/current/concepts/names.md
@@ -4,14 +4,14 @@ title: Starwhale中的命名规则
 
 下文的命名是指对Starwhale中的项目、模型、数据集、运行时以及版本标签进行命名。
 
-# 1. 名称限制
+## 1. 名称限制
 
 - 名称不区分大小写。
 - 名称必须仅由大小写字母“A-Z a-z”、数字“0-9”、连字符“-”、点“.”和下划线“_”组成。
 - 名称应始终以字母或“_”字符开头。
 - 名称的最大长度为80。
 
-# 2. 名称唯一性要求
+## 2. 名称唯一性要求
 
 资源名称在其所影响范围内必须是唯一的。例如，项目名称在实例中必须是唯一的，模型名称在其所在项目中必须是唯一的。
 

diff --git a/docs/i18n/zh/docusaurus-plugin-content-docs/current/concepts/project.md b/docs/i18n/zh/docusaurus-plugin-content-docs/current/concepts/project.md
@@ -6,7 +6,7 @@ title: Starwhale中的项目
 
 您可以将项目用于不同的目的。例如，您可以为数据科学家团队、产品线或特定模型创建项目。用户通常在日常工作中会参与一个或多个项目。
 
-Starwhale Server/Cloud项目按账号分组。Starwhale Standalone没有帐号概念。所以你不会在Starwhale Standalone项目中看到任何帐号前缀。
+Starwhale Server/Cloud项目按账号分组。Starwhale Standalone没有帐号概念。所以您不会在Starwhale Standalone项目中看到任何帐号前缀。
 
 Starwhale Server/Cloud项目可以是“公共”或“私有”。公共项目意味着同一实例上的所有用户在默认情况下都自动成为该项目的“访客”角色。有关角色的更多信息，请参阅[Starwhale中的角色和权限](roles-permissions)
 

diff --git a/docs/i18n/zh/docusaurus-plugin-content-docs/current/dataset/concepts.md b/docs/i18n/zh/docusaurus-plugin-content-docs/current/dataset/concepts.md
@@ -175,7 +175,7 @@ def iter_item():
 
 ### 5.1 文件类数据的处理方式
 
-Starwhale Dataset对文件类型的数据进行了特殊处理，用户如果你不关心Starwhale的实现方式，可以忽略本小节。
+Starwhale Dataset对文件类型的数据进行了特殊处理，如果您不关心Starwhale的实现方式，可以忽略本小节。
 
 根据实际使用场景，Starwhale Dataset 对基类为`starwhale.BaseArtifact`的文件类数据有三种处理方式：
 

diff --git a/docs/i18n/zh/docusaurus-plugin-content-docs/current/evaluation/concepts.md b/docs/i18n/zh/docusaurus-plugin-content-docs/current/evaluation/concepts.md
@@ -58,7 +58,7 @@ job-step-task 的抽象是实现 `Starwhale Evaluation` 分布式运行的基础
 
 ### 4.1 覆盖step配置
 
-你可以在创建job的时候提交一个yaml来覆盖在`swmp`中硬编码的step配置。`resources`字段的行为与[K8S容器与pod的资源管理](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/)中描述的一样。
+您可以在创建job的时候提交一个yaml来覆盖在`swmp`中硬编码的step配置。`resources`字段的行为与[K8S容器与pod的资源管理](https://kubernetes.io/docs/concepts/configuration/manage-resources-containers/)中描述的一样。
 
 ```yaml
   - job_name: default

diff --git a/docs/i18n/zh/docusaurus-plugin-content-docs/current/getting-started/cloud.md b/docs/i18n/zh/docusaurus-plugin-content-docs/current/getting-started/cloud.md
@@ -2,40 +2,40 @@
 title: Starwhale Cloud入门指南
 ---
 
-Starwhale Cloud运行在[AWS](https://cloud.starwhale.ai)和[阿里云](https://cloud.starwhale.cn)上。 这是两个相互独立的实例。 帐户和数据不共享。 你可以选择任何一个开始。
+Starwhale Cloud运行在[AWS](https://cloud.starwhale.ai)和[阿里云](https://cloud.starwhale.cn)上。 这是两个相互独立的实例。 帐户和数据不共享。 您可以选择任何一个开始。
 
-在开始之前，您需要先安装[Starwhale命令行工具(SWCLI)](../swcli)。
+在开始之前，您需要先安装[Starwhale Client（SWCLI）](../swcli)。
 
-# 1. 注册Starwhale Cloud并创建您的第一个项目
+## 1. 注册Starwhale Cloud并创建您的第一个项目
 
 您可以直接使用自己的GitHub或Google帐号登录，也可以注册一个新的帐号。如果您使用 GitHub 或 Google帐号登录，系统会要求您提供用户名。更多信息参见【Starwhale Cloud用户指南-创建账户】(../starwhale-cloud/index)
 
-然后你可以创建一个新项目。在本教程中，我们将使用名称“demo”作为项目名称。
+然后您可以创建一个新项目。在本教程中，我们将使用名称“demo”作为项目名称。
 
-# 2. 在本地机器上构建数据集、模型和运行时
+## 2. 在本地机器上构建数据集、模型和运行时
 
 按照[Starwhale Standalone入门指南](standalone)中的步骤1到步骤4在本地机器上创建：
 
 - 一个名为mnist的Starwhale模型
 - 一个名为mnist的Starwhale数据集
 - 一个名为pytorch的Starwhale运行时
 
-# 3.登录云实例
+## 3.登录云实例
 
 ```bash
 swcli instance login --username <您的用户名> --password <您的密码> --alias swcloud https://cloud.starwhale.ai
 # 如果您选择使用Starwhale Cloud CN，请将URL替换为https://cloud.starwhale.cn
 ```
 
-# 4. 将数据集、模型和运行时复制到Starwhale Cloud
+## 4. 将数据集、模型和运行时复制到Starwhale Cloud
 
 ```bash
 swcli model copy mnist/version/latest swcloud/project/demo
 swcli dataset copy mnist/version/latest swcloud/project/demo
 swcli runtime copy pytorch/version/latest swcloud/project/demo
 ```
 
-# 5.使用 Web UI 运行评估
+## 5.使用 Web UI 运行评估
 
 ![console-create-job.gif](../img/console-create-job.gif)
 

diff --git a/docs/i18n/zh/docusaurus-plugin-content-docs/current/getting-started/index.md b/docs/i18n/zh/docusaurus-plugin-content-docs/current/getting-started/index.md
@@ -2,7 +2,7 @@
 title: 入门指南
 ---
 
-首先，您需要安装[Starwhale命令行工具(SWCLI)](../swcli)，可以通过运行以下命令来完成command
+首先，您需要安装[Starwhale Client（SWCLI）](../swcli)，可以通过运行以下命令来完成command
 
 ```bash
 python3 -m pip install starwhale