huggingface-hub

name	huggingface-hub
description	HuggingFace hf CLI: search/download/upload models, datasets.
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.

Spaces MCP Caution

Treat Hugging Face Spaces MCP integrations as volatile:

• Configure and verify one Space at a time; multi-space MCP configurations can connect while exposing no usable tools.

• Create the configured work directory before relying on the server.

• Test each Space with a real tool call before using it in a workflow; search visibility does not prove the Gradio endpoint works.

• Check direct Gradio MCP endpoints before concluding the wrapper surface is limited: /gradio_api/mcp/sse and /gradio_api/mcp/http can expose richer toolsets than a generated adapter.

• Validate the response shape of each tool. Spaces often expose heterogeneous strings, JSON-like dictionaries, binary artifacts, or disabled endpoints behind similar client calls.

• Bound request size, timeout, retry, and cache behavior explicitly. Space latency, GPU quota, and cold starts are part of the integration contract.

• Treat working-space lists as stale quickly. Re-run discovery and a live smoke call before reporting that a Space is available.

For MCP-specific tool-surface design, use the native-mcp skill and its references/tool-interface-design.md note.

Spaces MCP Caution

Treat Hugging Face Spaces MCP integrations as volatile:

• Configure and verify one Space at a time; multi-space MCP configurations can connect while exposing no usable tools.
• Create the configured work directory before relying on the server.
• Test each Space with a real tool call before using it in a workflow; search visibility does not prove the Gradio endpoint works.
• Check direct Gradio MCP endpoints before concluding the wrapper surface is limited: /gradio_api/mcp/sse and /gradio_api/mcp/http can expose richer toolsets than a generated adapter.
• Validate the response shape of each tool. Spaces often expose heterogeneous strings, JSON-like dictionaries, binary artifacts, or disabled endpoints behind similar client calls.
• Bound request size, timeout, retry, and cache behavior explicitly. Space latency, GPU quota, and cold starts are part of the integration contract.
• Treat working-space lists as stale quickly. Re-run discovery and a live smoke call before reporting that a Space is available.

For MCP-specific tool-surface design, use the native-mcp skill and its references/tool-interface-design.md note.

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.