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huggingface-hub

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

Updated Jul 7, 2026
Search Tags:#automation#repositories#datasets#hugging face#hf cli#inference endpoints#mlo
One-click install
npx skills add https://github.com/TitoPrausee/nexus-toti --skill huggingface-hub-titoprausee
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: huggingface-hub
Source: https://github.com/TitoPrausee/nexus-toti/tree/main/data/skills/mlops/huggingface-hub
Command: npx skills add https://github.com/TitoPrausee/nexus-toti --skill huggingface-hub-titoprausee

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill removes the friction of managing Hugging Face Hub resources by giving you one place to search, download, upload, and administer models, datasets, Spaces, buckets, and related infrastructure.

Core Features & Use Cases

  • Repository Management: Create, delete, move, duplicate, and organize Hub repositories and Git-like references.
  • Data and Model Operations: Download artifacts, upload files or large folders, inspect models and datasets, and run SQL queries over dataset parquet sources.
  • Platform Automation: Deploy inference endpoints, manage jobs, control Spaces, handle webhooks, and automate bucket or cache workflows.
  • Use Case: A machine learning engineer can publish a trained model, verify dataset metadata, deploy an endpoint, and keep the workflow synchronized from a single command-line interface.

Quick Start

Use the huggingface-hub skill to help me authenticate with Hugging Face and manage a model repository, including download, upload, and deployment steps.

Frequently Asked Questions about huggingface-hub

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

FAQPage Schema
How do I manage Hugging Face Hub repositories from the command line?▼

Hugging Face Hub repository management from the command line lets you create, delete, move, and duplicate repositories. You can execute these administrative actions alongside model and dataset operations using a single CLI interface.

Can I upload large folders to Hugging Face datasets using the hf CLI?▼

Uploading large folders to Hugging Face datasets is supported directly via the hf CLI. The interface handles large-folder transfers reliably when you upload files or artifacts to your target repositories.

How does querying Hugging Face datasets with SQL work?▼

Querying Hugging Face datasets with SQL works by running queries over the parquet sources of the datasets. You can inspect dataset metadata and execute SQL queries directly from the command line to extract specific data.

Do I need an HF token to deploy inference endpoints and manage MLOps?▼

An HF token is required to deploy inference endpoints and manage MLOps workflows. Token authentication ensures reliable access for endpoint deployment, job execution, and webhook automation across your Hub resources.

What is the best way to automate Hugging Face Spaces and webhook workflows?▼

Automating Hugging Face Spaces and webhook workflows is best handled through CLI commands that control Spaces and manage webhooks. This approach provides machine-readable output for seamless platform automation and synchronization.

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