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huggingface-hub

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

1|Updated Apr 10, 2026
Search Tags:#deployment#models#cli#datasets#spaces#hub#hugging face
One-click install
npx skills add https://github.com/zerwiz/wayofpi --skill huggingface-hub-zerwiz
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: huggingface-hub
Source: https://github.com/zerwiz/wayofpi/tree/main/.hermes/hermes-agent/skills/mlops/huggingface-hub
Command: npx skills add https://github.com/zerwiz/wayofpi --skill huggingface-hub-zerwiz

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill removes the friction of managing Hugging Face Hub resources by centralizing model, dataset, Space, bucket, endpoint, and job operations into one command-line workflow.

Core Features & Use Cases

  • Repository Operations: Create, delete, move, branch, tag, duplicate, and clean up Hub repositories.
  • Data and Model Access: Search, inspect, download, and upload datasets and models with authenticated Hub access.
  • MLOps Automation: Query datasets with SQL, manage discussions and pull requests, deploy inference endpoints, and control Spaces, jobs, buckets, and webhooks.
  • Use Case: A machine learning engineer can fetch a model checkpoint, publish a fine-tuned version, query dataset parquet files, and deploy an endpoint without leaving the terminal.

Quick Start

Use this Skill to help you authenticate with Hugging Face and perform the exact hf command needed for your Hub task.

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?▼

You can manage Hugging Face Hub repositories from the command line by automating repository creation, deletion, branching, and tagging. This Skill centralizes model, dataset, and Space operations into a single CLI workflow.

Can I deploy inference endpoints and Spaces using a CLI?▼

Yes, you can deploy inference endpoints and control Spaces using a CLI. This Skill supports infrastructure operations for machine learning teams, enabling deployment control directly from the terminal.

Do I need a Hugging Face token to download and upload models?▼

Yes, you need a valid Hugging Face token to download and upload models. Authenticated Hub access is required to perform reproducible file transfers, repository administration, and data synchronization.

What is the best way to query Hugging Face datasets with SQL?▼

The best way to query Hugging Face datasets with SQL is through an automated CLI workflow. This Skill allows you to query dataset parquet files and manage MLOps pipelines without leaving the terminal.

Does Hugging Face Hub CLI support managing discussions and pull requests?▼

Yes, Hugging Face Hub CLI supports managing discussions and pull requests. This Skill automates discussion workflows and repository administration, streamlining collaboration for MLOps teams.

What are the limitations of using CLI for Hub repository management?▼

Limitations of using CLI for Hub repository management include requiring the hf CLI, a valid token, and appropriate permissions. Without these, you cannot perform file transfers, deployment control, or storage synchronization.

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