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hf-cli

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

2|Updated Mar 29, 2026
Search Tags:#automation#cli#machine learning#inference#model management#huggingface
One-click install
npx skills add https://github.com/NagyVikt/codex-plugins --skill hf-cli-nagyvikt
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: hf-cli
Source: https://github.com/NagyVikt/codex-plugins/tree/main/plugins/hugging-face/skills/cli
Command: npx skills add https://github.com/NagyVikt/codex-plugins --skill hf-cli-nagyvikt

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This skill simplifies the management of Hugging Face Hub resources, replacing the deprecated legacy CLI with a unified, efficient interface for handling models, datasets, and spaces.

Core Features & Use Cases

  • Resource Management: Seamlessly download, upload, and sync repositories, models, and datasets between local environments and the Hub.
  • Infrastructure Control: Manage Inference Endpoints, remote Jobs, and webhooks directly from your terminal.
  • Use Case: A machine learning engineer can use this skill to automate the deployment of a model to an Inference Endpoint or trigger a remote training job without leaving their development environment.

Quick Start

Use the hf-cli skill to list all available models on the Hugging Face Hub that match the search term sentiment.

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 Hub repositories and models from the terminal?▼

You can manage Hugging Face Hub repositories and models from the terminal by using a CLI interface that handles downloading, uploading, and syncing resources directly between your local environment and the Hub.

Can I automate deployment to Hugging Face Inference Endpoints via command line?▼

Yes, you can automate deployment to Hugging Face Inference Endpoints via command line. The CLI provides infrastructure control to manage endpoints, trigger remote jobs, and configure webhooks without leaving your development environment.

What is the best way to sync datasets to the Hugging Face Hub locally?▼

The best way to sync datasets to the Hugging Face Hub locally is through a unified CLI that replaces the deprecated legacy interface, enabling seamless dataset operations and repository synchronization for AI development workflows.

Does the Hugging Face CLI support secure authentication and cache management?▼

Yes, the Hugging Face CLI supports secure authentication and cache management. It provides standardized commands for secure access and local cache handling to streamline your machine learning workflows.

How do I list and search for Hugging Face models matching a specific term?▼

To list Hugging Face models matching a specific term, you can use the CLI's search functionality. For example, running the appropriate command with a search term like 'sentiment' will return all available models on the Hub matching that query.

Are there limitations when triggering remote training jobs on the Hugging Face Hub?▼

While the CLI facilitates remote job execution and infrastructure orchestration, limitations depend on your Hugging Face Hub account permissions and the underlying infrastructure availability for remote training jobs.

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