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Documentation:https://hf.co/docs/huggingface_hub

Source Code:https://github.com/huggingface/huggingface_hub

Thehuggingface_hub library allows you to interact with theHugging Face Hub, a platform democratizing open-source Machine Learning for creators and collaborators. Discover pre-trained models and datasets for your projects or play with the thousands of machine learning apps hosted on the Hub. You can also create and share your own models, datasets and demos with the community. Thehuggingface_hub library provides a simple way to do all these things with Python.

• Download files from the Hub.
• Upload files to the Hub.
• Manage your repositories.
• Run Inference on deployed models.
• Search for models, datasets and Spaces.
• Share Model Cards to document your models.
• Engage with the community through PRs and comments.

Install thehuggingface_hub package withpip:

pip install huggingface_hub

If you prefer, you can also install it withconda.

In order to keep the package minimal by default,huggingface_hub comes with optional dependencies useful for some use cases. For example, if you want have a complete experience for Inference, run:

pip install huggingface_hub[inference]

To learn more installation and optional dependencies, check out theinstallation guide.

Download a single file

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

Or an entire repository

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

Files will be downloaded in a local cache folder. More details inthis guide.

The Hugging Face Hub uses tokens to authenticate applications (seedocs). To log in your machine, run the following CLI:

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

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

Upload a single file

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

Or an entire folder

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

For details in theupload guide.

We're partnering with cool open source ML libraries to provide free model hosting and versioning. You can find the existing integrationshere.

The advantages are:

• Free model or dataset hosting for libraries and their users.
• Built-in file versioning, even with very large files, thanks to a git-based approach.
• In-browser widgets to play with the uploaded models.
• Anyone can upload a new model for your library, they just need to add the corresponding tag for the model to be discoverable.
• Fast downloads! We use Cloudfront (a CDN) to geo-replicate downloads so they're blazing fast from anywhere on the globe.
• Usage stats and more features to come.

If you would like to integrate your library, feel free to open an issue to begin the discussion. We wrote astep-by-step guide with ❤️ showing how to do this integration.

Everyone is welcome to contribute, and we value everybody's contribution. Code is not the only way to help the community.Answering questions, helping others, reaching out and improving the documentations are immensely valuable to the community.We wrote acontribution guide to summarizehow to get started to contribute to this repository.