The Hugging Face Hub Python client is a library that provides programmatic access to the Hugging Face Hub, a centralized platform for hosting and collaborating on machine learning models, datasets, and demo applications. It serves as the primary SDK for interacting with the Hub's API, enabling users to download and upload models and datasets, manage repositories, authenticate via tokens or OAuth, and run inference on hosted models through a unified interface.
The client distinguishes itself through a comprehensive set of capabilities that go beyond basic file transfer. It includes a CLI extension system for adding custom commands, chunk-based deduplication for accelerated downloads, server-side file operations that avoid local transfers, and a virtual filesystem mounting feature that exposes remote Hub files as a local directory. The library also supports OIDC token exchange for CI/CD workflows, webhook management for event-driven automation, and the ability to execute cloud compute jobs on remote GPUs or TPUs.
Beyond its core storage and authentication features, the client offers tools for managing the full lifecycle of Hub resources. This includes creating and configuring Spaces for interactive demos, deploying and scaling inference endpoints, managing S3-like object storage buckets, and participating in community discussions and pull requests. The library also provides search and discovery capabilities for browsing models, datasets, and Spaces by task, framework, or author, along with cache management utilities for inspecting, pruning, and verifying the integrity of locally stored files.
The client is installed via pip or conda and supports configuration for HTTP proxies and custom Hub endpoint overrides, making it adaptable to network-restricted or self-hosted environments.
