hf-cli

Manage Hugging Face Hub models, datasets, and spaces via command-line interface.

3|Updated Apr 2, 2026

Search Tags:#deployment #models #cli #machine learning #datasets #huggingface

Ready to run

npx skills add https://github.com/legout/pi-config --skill hf-cli-legout

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: hf-cli
Source: https://github.com/legout/pi-config/tree/main/installed-skills/hf-cli
Command: npx skills add https://github.com/legout/pi-config --skill hf-cli-legout

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill simplifies the management of the Hugging Face ecosystem by providing a unified interface for authentication, repository management, and cloud infrastructure tasks, removing the need for manual web-based interactions.

Core Features & Use Cases

Hub Management: Seamlessly download, upload, and manage models, datasets, and spaces directly from your terminal.
Cloud Infrastructure: Deploy and scale Inference Endpoints and manage scheduled jobs on Hugging Face infrastructure.
Use Case: Use this skill to quickly authenticate your session, list your available datasets, and deploy a model to an Inference Endpoint without leaving your coding environment.

Quick Start

Use the hf-cli skill to list all models available under the current user account.

Frequently Asked Questions about hf-cli

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I manage Hugging Face models and datasets from the command line?▼

You can manage Hugging Face models and datasets from the command line by using a CLI interface to download, upload, and handle repositories directly from your terminal. It provides a unified terminal-based Hub management experience.

Can I deploy Hugging Face Inference Endpoints without using the web interface?▼

Yes, you can deploy and scale Hugging Face Inference Endpoints without the web interface by using a CLI skill. It enables programmatic control to deploy cloud infrastructure and schedule jobs directly from your terminal.

What is the best way to authenticate my session for Hugging Face machine learning workflows?▼

The best way to authenticate your session for Hugging Face machine learning workflows is using a CLI skill. It facilitates quick session authentication, allowing you to interact with the Hub without manual web-based interactions.

How do I list all my available datasets on the Hugging Face Hub?▼

To list all your available datasets on the Hugging Face Hub, use a CLI skill designed for Hub interaction. It allows you to authenticate your session and programmatically list datasets available under your current user account.

Does Hugging Face CLI support managing repository settings and discussions?▼

Yes, the Hugging Face CLI supports managing repository settings and discussions. It provides comprehensive programmatic control over repository configurations and Hub discussions as part of its core machine learning workflow features.

Can I maintain local cache for Hugging Face machine learning models via the terminal?▼

Yes, you can maintain local cache for Hugging Face machine learning models via the terminal. The CLI interface includes local cache maintenance features to help manage your downloaded models and datasets efficiently.