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huggingface-hub

Hugging Face Hub CLI (hf) — 모델/데이터셋 검색, 다운로드, 업로드, Space 관리

Hugging Face
MIT

Hugging Face CLI (hf) Reference Guide

The hf command is the modern command-line interface for interacting with the Hugging Face Hub, providing tools to manage repositories, models, datasets, and Spaces.

IMPORTANT: The hf command replaces the now deprecated huggingface-cli command.

Quick Start


* Installation: curl -LsSf https://hf.co/cli/install.sh | bash -s
* Help: Use hf --help to view all available functions and real-world examples.
* Authentication: Recommended via HF_TOKEN environment variable or the --token flag.


Core Commands

General Operations


* hf download REPO_ID: Download files from the Hub.
* hf upload REPO_ID: Upload files/folders (recommended for single-commit).
* hf upload-large-folder REPO_ID LOCAL_PATH: Recommended for resumable uploads of large directories.
* hf sync: Sync files between a local directory and a bucket.
* hf env / hf version: View environment and version details.

Authentication (hf auth)


* login / logout: Manage sessions using tokens from huggingface.co/settings/tokens.
* list / switch: Manage and toggle between multiple stored access tokens.
* whoami: Identify the currently logged-in account.

Repository Management (hf repos)


* create / delete: Create or permanently remove repositories.
* duplicate: Clone a model, dataset, or Space to a new ID.
* move: Transfer a repository between namespaces.
* branch / tag: Manage Git-like references.
* delete-files: Remove specific files using patterns.


Specialized Hub Interactions

Datasets & Models


* Datasets: hf datasets list, info, and parquet (list parquet URLs).
* SQL Queries: hf datasets sql SQL — Execute raw SQL via DuckDB against dataset parquet URLs.
* Models: hf models list and info.
* Papers: hf papers list — View daily papers.

Discussions & Pull Requests (hf discussions)


* Manage the lifecycle of Hub contributions: list, create, info, comment, close, reopen, and rename.
* diff: View changes in a PR.
* merge: Finalize pull requests.

Infrastructure & Compute


* Endpoints: Deploy and manage Inference Endpoints (deploy, pause, resume, scale-to-zero, catalog).
* Jobs: Run compute tasks on HF infrastructure. Includes hf jobs uv for running Python scripts with inline dependencies and stats for resource monitoring.
* Spaces: Manage interactive apps. Includes dev-mode and hot-reload for Python files without full restarts.

Storage & Automation


* Buckets: Full S3-like bucket management (create, cp, mv, rm, sync).
* Cache: Manage local storage with list, prune (remove detached revisions), and verify (checksum checks).
* Webhooks: Automate workflows by managing Hub webhooks (create, watch, enable/disable).
* Collections: Organize Hub items into collections (add-item, update, list).


Advanced Usage & Tips

Global Flags


* --format json: Produces machine-readable output for automation.
* -q / --quiet: Limits output to IDs only.

Extensions & Skills


* Extensions: Extend CLI functionality via GitHub repositories using hf extensions install REPO_ID.
* Skills: Manage AI assistant skills with hf skills add.

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