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KarlinskyS
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huggingface-hub

Search, download, and upload models, datasets, and spaces on Hugging Face Hub.

Updated Apr 10, 2026
Search Tags:#deployment#cli#mlops#model#dataset#huggingface#hub
One-click install
npx skills add https://github.com/KarlinskyS/hermesSkills --skill huggingface-hub-karlinskys
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: huggingface-hub
Source: https://github.com/KarlinskyS/hermesSkills/tree/main/mlops/huggingface-hub
Command: npx skills add https://github.com/KarlinskyS/hermesSkills --skill huggingface-hub-karlinskys

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Managing, versioning, and sharing machine learning models, datasets, and Spaces on the Hugging Face Hub can be cumbersome without a unified command-line interface.

Core Features & Use Cases

  • Model and Dataset Management: List, download, upload, and organize assets directly from the hub.
  • Repository Operations: Create, delete, duplicate, and move repositories with Git‑like controls.
  • Inference & Deployment: Deploy, pause, and scale inference endpoints; manage Spaces and compute jobs.
  • Automation: Use buckets, webhooks, and collections to streamline workflows and integrate with CI/CD pipelines.
  • Use Case Example: A data science team can script automated model versioning and dataset syncing across environments using the hf CLI.

Quick Start

Ask the assistant to list all models you own on Hugging Face with a single command.

Frequently Asked Questions about huggingface-hub

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

FAQPage Schema
How do I download and upload models or datasets from Hugging Face Hub using the command line?▼

You can download and upload models or datasets from Hugging Face Hub using the `hf` CLI tool. It provides Git-like controls to list, transfer, and organize repository assets directly from your terminal.

Can I deploy and manage Hugging Face inference endpoints through a CLI?▼

Yes, you can deploy, pause, and scale Hugging Face inference endpoints through the CLI. It also manages Spaces and compute jobs, streamlining machine learning deployment workflows.

Do I need authentication tokens to manage Hugging Face repositories?▼

Yes, you need appropriate authentication tokens to perform repository operations, data transfers, and endpoint management on Hugging Face Hub using the `hf` CLI tool.

What is the best way to automate dataset syncing and model versioning across environments?▼

The best way to automate dataset syncing and model versioning is by scripting the `hf` CLI tool. It integrates with CI/CD pipelines using buckets, webhooks, and collections to streamline workflows.

Does the Hugging Face CLI support repository operations like creating and deleting repos?▼

Yes, the Hugging Face CLI supports repository operations including creating, deleting, duplicating, and moving repositories with Git-like controls for collaborative sharing across teams.

Why use a command line interface for Hugging Face Hub instead of the web interface?▼

Using a command line interface for Hugging Face Hub solves the cumbersome nature of managing and versioning machine learning assets. It enables automated model versioning and dataset syncing across environments.

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