huggingface/huggingface_hub
The official CLI and Python client for the Hugging Face Hub.
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문서
- BucketsBuckets provide S3-like object storage on Hugging Face, powered by the Xet storage backend. Unlike repositories (which are git-based and track file history), buckets are remote object storage contain…docs/source/en/guides/buckets.md
- Create a CLI extensionThe hf CLI supports extensions, custom commands provided by the community that integrate seamlessly into the CLI. Extensions are hosted as public GitHub repositories and can be installed with a singl…docs/source/en/guides/cli-extensions.md
- Command Line Interface (CLI)The huggingface_hub Python package comes with a built-in CLI called hf. This tool allows you to interact with the Hugging Face Hub directly from a terminal. For example, you can log in to your accoun…docs/source/en/guides/cli.md
- CollectionsA collection is a group of related items on the Hub (models, datasets, Spaces, papers, collections, buckets) that are organized together on the same page. Collections are useful for creating your own…docs/source/en/guides/collections.md
- Interact with Discussions and Pull RequestsThe huggingface_hub library provides a Python interface to interact with Pull Requests and Discussions on the Hub. Visit the dedicated documentation page for a deeper view of what Discussions and Pul…docs/source/en/guides/community.md
- Download files from the HubThe huggingface_hub library provides functions to download files from the repositories stored on the Hub. You can use these functions independently or integrate them into your own library, making it…docs/source/en/guides/download.md
- Interact with the Hub through the Filesystem APIIn addition to the [HfApi], the huggingface_hub library provides [HfFileSystem], a pythonic fsspec-compatible file interface to the Hugging Face Hub. The [HfFileSystem] builds on top of the [HfApi] a…docs/source/en/guides/hf_file_system.md
- Run Inference on serversInference is the process of using a trained model to make predictions on new data. Because this process can be compute-intensive, running on a dedicated or external service can be an interesting opti…docs/source/en/guides/inference.md
- Inference EndpointsInference Endpoints provides a secure production solution to easily deploy any transformers, sentence-transformers, and diffusers models on a dedicated and autoscaling infrastructure managed by Huggi…docs/source/en/guides/inference_endpoints.md
- Integrate any ML framework with the HubThe Hugging Face Hub makes hosting and sharing models with the community easy. It supports dozens of libraries in the Open Source ecosystem. We are always working on expanding this support to push co…docs/source/en/guides/integrations.md
- Run and manage JobsThe Hugging Face Hub provides compute for AI and data workflows via Jobs.docs/source/en/guides/jobs.md
- Understand cachinghuggingface_hub uses a local file-based cache to store individual files downloaded from the Hub and avoid downloading unchanged files again when a repo gets updated. In addition, hf_xet stores a shar…docs/source/en/guides/manage-cache.md
- Manage your SpaceIn this guide, we will see how to manage your Space runtime (secrets, hardware, and volumes) using huggingface_hub.docs/source/en/guides/manage-spaces.md
- Create and share Model CardsThe huggingface_hub library provides a Python interface to create, share, and update Model Cards. Visit the dedicated documentation page for a deeper view of what Model Cards on the Hub are, and how…docs/source/en/guides/model-cards.md
- How-to guidesIn this section, you will find practical guides to help you achieve a specific goal. Take a look at these guides to learn how to use huggingface_hub to solve real-world problems:docs/source/en/guides/overview.md
- Create and manage a repositoryThe Hugging Face Hub is a collection of git repositories. Git is a widely used tool in software development to easily version projects when working collaboratively. This guide will show you how to in…docs/source/en/guides/repository.md
- SandboxesA sandbox is an isolated cloud machine you can spin up in seconds, run commands in with live-streamed output, and move files in and out of — all from Python or the CLI. Sandboxes are built on top of…docs/source/en/guides/sandbox.md
- Search the HubIn this tutorial, you will learn how to search models, datasets and spaces on the Hub using huggingface_hub.docs/source/en/guides/search.md
- Upload files to the HubSharing your files and work is an important aspect of the Hub. The huggingface_hub offers several options for uploading your files to the Hub. You can use these functions independently or integrate t…docs/source/en/guides/upload.md
- WebhooksWebhooks are a foundation for MLOps-related features. They allow you to listen for new changes on specific repos or to all repos belonging to particular users/organizations you're interested in follo…docs/source/en/guides/webhooks.md
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