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huggingface-spaces

Create and deploy ML apps on Hugging Face Spaces with Gradio, Docker, or Static.

10.9k|724|Updated Nov 24, 2025
Search Tags:#machine learning#model management#app deployment#Gradio#Hugging Face Spaces
One-click install
npx skills add https://github.com/huggingface/skills --skill huggingface-spaces-huggingface
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: huggingface-spaces
Source: https://github.com/huggingface/skills/tree/main/skills/huggingface-spaces
Command: npx skills add https://github.com/huggingface/skills --skill huggingface-spaces-huggingface

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires hf-cli, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill facilitates the creation, deployment, and maintenance of machine learning applications on Hugging Face Spaces, enabling users to build and host ML applications efficiently.

Core Features & Use Cases

  • Space Creation: Build Spaces using different SDKs like Gradio, Docker, or Static.
  • App Deployment: Deploy applications with support for ZeroGPU and dedicated GPUs.
  • Model Management: Handle model loading, debugging, and inference providers.
  • Use Case: For a developer looking to create a Gradio app for image classification, this Skill provides the necessary guidance to set up the Space, build the app, and deploy it on Hugging Face Spaces.

Quick Start

Use the 'huggingface-spaces' skill to create a new Space for your image classification app.

Frequently Asked Questions about huggingface-spaces

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

FAQPage Schema
How do I deploy a Gradio app on Hugging Face Spaces?▼

To deploy a Gradio app on Hugging Face Spaces, you can use this Skill to create a new Space, configure the Gradio SDK, and host your machine learning application efficiently for inference.

Can I use dedicated GPUs or ZeroGPU for inference on Hugging Face Spaces?▼

Yes, deploying applications on Hugging Face Spaces supports both ZeroGPU and dedicated GPUs, enabling efficient hardware-accelerated inference for your machine learning models.

What SDKs are supported for creating machine learning applications on Hugging Face Spaces?▼

Hugging Face Spaces supports creating and deploying machine learning applications using Gradio, Docker, and Static SDKs, allowing flexible environment setup depending on your app requirements.

Do I need the hf-cli skill to manage model deployment on Hugging Face Spaces?▼

Yes, you need the 'hf-cli' skill as a prerequisite to handle authentication and command execution when creating, deploying, and maintaining your machine learning applications on Spaces.

How does Docker support work when building apps on Hugging Face Spaces?▼

Docker support on Hugging Face Spaces allows you to build and deploy customized machine learning application environments, providing flexible containerized solutions alongside Gradio and Static SDKs.

What is the best way to handle model loading and debugging for Hugging Face Spaces apps?▼

This Skill provides model management capabilities to handle model loading, debugging, and inference providers directly within your Hugging Face Spaces deployment workflow.

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