hermes-sync/skills/mlops/huggingface-hub/SKILL.md

name, description, version, author, license, tags

name	description	version	author	license	tags
huggingface-hub	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.	1.0.0	Hugging Face	MIT	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.