| name | huggingface-hub |
| description | Hugging Face Hub CLI (hf) — search, download, and upload models and datasets, manage repos, query datasets with SQL, deploy inference endpoints, manage Spaces and buckets. |
| version | 1.0.0 |
| author | Hugging Face |
| license | MIT |
| tags | ["huggingface","hf","models","datasets","hub","mlops"] |
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.