hf-cli

Manage Hugging Face Hub repositories, models, and datasets via CLI.

3|Updated Mar 26, 2026

Search Tags:#cli #repository #model management #dataset #huggingface #ML deployment

Ready to run

npx skills add https://github.com/marcoshernanz/llm-lab --skill hf-cli-marcoshernanz

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: hf-cli
Source: https://github.com/marcoshernanz/llm-lab/tree/main/.agents/skills/hf-cli
Command: npx skills add https://github.com/marcoshernanz/llm-lab --skill hf-cli-marcoshernanz

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires huggingface_hub, and includes scripts (resource) components.

What problem does it solve?

This Skill streamlines the interaction with the Hugging Face Hub, enabling users to download, upload, and manage repositories, models, datasets, and Spaces seamlessly.

Core Features & Use Cases

Repository Management: Create, delete, and clone repositories on Hugging Face with simple commands.
Model and Dataset Handling: List, get info, and upload models and datasets to the Hub.
Use Case: A data scientist wants to update a model's metadata and share a new dataset; this Skill provides all necessary commands in a unified CLI.

Quick Start

Use the hf-cli skill to list available models on the Hugging Face Hub.

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 repositories from the command line?▼

You can manage Hugging Face repositories from the command line by using this interface to create, delete, and clone repos. It provides simple commands to handle repository version control directly from your terminal.

Can I upload and download Hugging Face datasets and models using a CLI?▼

Yes, you can upload and download Hugging Face datasets and models using a CLI. This skill provides commands to list, get information, and publish or retrieve models and datasets to streamline Hub interactions.

Do I need the huggingface_hub library to automate ML deployment workflows?▼

Yes, you need the huggingface_hub library installed to automate ML deployment workflows. This skill requires the library as a dependency to facilitate seamless integration into your automation pipeline.

What is the best way to update model metadata and share datasets on Hugging Face?▼

The best way to update model metadata and share datasets on Hugging Face is using a unified CLI. It allows data scientists to execute all necessary publication and management commands within a single interface.

Does this CLI tool support listing available models on the Hugging Face Hub?▼

Yes, this CLI tool supports listing available models on the Hugging Face Hub. You can quickly start using the skill to retrieve model information and list assets directly through simple command execution.