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README
Apache-2.0


huggingface_hub library logo

Hugging Face Hub Python 客户端

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文档: <a href="https://hf.co/docs/huggingface_hub" target="_blank">https://hf.co/docs/huggingface_hub </a>

源代码: <a href="https://github.com/huggingface/huggingface_hub" target="_blank">https://github.com/huggingface/huggingface_hub </a>


欢迎使用 Hugging Face Hub 库

通过huggingface_hub 库,您可以与面向机器学习开发者和协作者的平台 Hugging Face Hub进行交互,找到适用于您所在项目的预训练模型和数据集,体验在平台托管的数百个机器学习应用,还可以创建或分享自己的模型和数据集并于社区共享。以上所有都可以用Python在huggingface_hub 库中轻松实现。

主要特点

安装

使用pip安装 huggingface_hub 包:

pip install huggingface_hub

如果您更喜欢,也可以使用 conda 进行安装

为了默认保持包的最小化,huggingface_hub 带有一些可选的依赖项,适用于某些用例。例如,如果您想要完整的推断体验,请运行:

pip install huggingface_hub[inference]

要了解更多安装和可选依赖项,请查看安装指南

快速入门指南

下载文件

下载单个文件,请运行以下代码:

from huggingface_hub import hf_hub_download

hf_hub_download(repo_id="tiiuae/falcon-7b-instruct", filename="config.json")

如果下载整个存储库,请运行以下代码:

from huggingface_hub import snapshot_download

snapshot_download("stabilityai/stable-diffusion-2-1")

文件将被下载到本地缓存文件夹。更多详细信息请参阅此 指南.

登录

Hugging Face Hub 使用令牌对应用进行身份验证(请参阅文档). 要登录您的机器,请运行以下命令行:

huggingface-cli login
# or using an environment variable
huggingface-cli login --token $HUGGINGFACE_TOKEN

创建一个存储库

要创建一个新存储库,请运行以下代码:

from huggingface_hub import create_repo

create_repo(repo_id="super-cool-model")

上传文件

上传单个文件,请运行以下代码

from huggingface_hub import upload_file

upload_file(
    path_or_fileobj="/home/lysandre/dummy-test/README.md",
    path_in_repo="README.md",
    repo_id="lysandre/test-model",
)

如果上传整个存储库,请运行以下代码:

from huggingface_hub import upload_folder

upload_folder(
    folder_path="/path/to/local/space",
    repo_id="username/my-cool-space",
    repo_type="space",
)

有关详细信息,请查看 上传指南.

集成到 Hub 中

我们正在与一些出色的开源机器学习库合作,提供免费的模型托管和版本控制。您可以在 这里找到现有的集成

优势包括:

  • 为库及其用户提供免费的模型或数据集托管
  • 内置文件版本控制,即使对于非常大的文件也能实现,这得益于基于 Git 的方法
  • 为所有公开可用的模型提供托管的推断 API
  • 在网页端可在线体验所有公开的模型
  • 任何人都可以上传新模型到您的库,他们只需为模型添加相应的标签,以便让其被发现
  • 快速下载!我们使用 Cloudfront(CDN)进行地理复制下载,因此无论在全球任何地方,下载速度都非常快。
  • 使用统计和更多功能即将推出

如果您想要集成您的库,请随时打开一个问题来开始讨论。我们编写了一份逐步指南,以❤️的方式展示如何进行这种集成。

欢迎各种贡献(功能请求、错误等) 💙💚💛💜🧡❤️

欢迎每个人来进行贡献,我们重视每个人的贡献。编写代码并非唯一的帮助社区的方式。回答问题、帮助他人、积极互动并改善文档对社区来说都是极其有价值的。为此我们编写了一份 贡献指南 以进行总结,即如何开始为这个存储库做贡献

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