huggingface-hub

Manage Hugging Face Hub models and datasets via command-line interface.

Updated Jun 13, 2026
One-click install
npx skills add https://github.com/srivtx/supercharger-opencode --skill huggingface-hub-srivtx
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: huggingface-hub
Source: https://github.com/srivtx/supercharger-opencode/tree/main/data/huggingface-hub
Command: npx skills add https://github.com/srivtx/supercharger-opencode --skill huggingface-hub-srivtx

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires huggingface-cli, and includes scripts (resource) components.

What problem does it solve?

This Skill streamlines the process of searching, downloading, uploading, and managing models and datasets from the Hugging Face Hub, simplifying machine learning operations.

Core Features & Use Cases

  • Model and Dataset Management: Perform operations like search, download, upload, and sync.
  • Authentication: Manage sessions using tokens and access different accounts.
  • Repository Management: Create, delete, duplicate, move, branch, tag, and delete files in repositories.
  • Use Case: Quickly access and utilize the latest machine learning models and datasets for your projects.

Quick Start

Install the Hugging Face CLI (hf) and download a model using hf download <model_id>.

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 models and datasets from the command line?

You can manage Hugging Face Hub models and datasets via the command line by installing the `huggingface-cli` to execute operations like search, download, upload, and sync directly from your terminal.

Do I need the huggingface-cli to download machine learning models?

Yes, you need the `huggingface-cli` installed to use this Skill. Once installed, you can quickly download machine learning models using the `hf download <model_id>` command.

Can I create and delete repositories on the Hugging Face Hub using a script?

Yes, you can create, delete, duplicate, move, branch, and tag Hugging Face Hub repositories. The Skill also supports managing files and authenticating sessions using tokens.

What is the best way to sync local datasets with Hugging Face repositories?

The best way to sync local datasets with Hugging Face repositories is using the command-line interface. It supports repository synchronization, allowing data scientists to efficiently manage and update Hub resources.

Does this Skill support authentication for different Hugging Face accounts?

Yes, the Skill supports authentication by managing sessions using tokens. This allows you to securely access and manage different Hugging Face accounts during your machine learning operations.