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huggingface-hub

Use the hf command-line tool to find, download, and upload models and datasets on Hugging Face Hub. The guide also covers repository management, hosted computing resources, local cache maintenance, and automation options.

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HuggingFace hf CLI: search/download/upload models, datasets.

Works withHugging Face
See how to install

Good for

  • Find and download models or datasets
  • Upload local files to the Hub
  • Create repositories and manage branches or tags
  • Review and clean the local cache
  • Deploy and manage Inference Endpoints

Files included (1)

  • SKILL.md3.6 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

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; also handles resumable uploads of large directories).
  • hf upload-large-folder REPO_ID LOCAL_PATH: [Deprecated] — use hf upload instead.
  • 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 ls — 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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