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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.

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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.

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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).

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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.