Hugging Face Spaces

When to Use

Use this skill when you need build, deploy, and maintain applications on Hugging Face Spaces — Gradio / Docker / Static SDKs, ZeroGPU and dedicated hardware, model loading, debugging, buckets, inference providers, community grants. Use whenever the user asks to create or host an app on Hugging Face, port existing code to a Space, diagnose build/runtime errors, or choose storage and inference hardware.

Hugging Face Spaces host machine-learning applications. Each Space has a git repository; live catalog totals change. This skill covers creating, building, debugging, and maintaining them.

Modified 2026-10-23: corrected eligibility/version assumptions, deployment/testing boundaries, storage/privacy and dependency recipes. Apache-2.0 upstream attribution is retained.

0. Getting ready

Before anything else:

1. Check the hf CLI is installed: which hf. If not, pip install -U huggingface_hub.
2. Check the user is logged in: hf auth whoami. If not, ask them to authenticate locally with hf auth login; never paste the token into chat or logs — they'll need a write-scoped token from https://huggingface.co/settings/tokens.
3. Note whoami's canPay and isPro flags — they gate hardware choices below.

The hf-cli skill teaches an agent every hf command and is the recommended companion to this one. Install it with hf skills add hf-cli (add --claude --global to install for Claude Code as well, user-level).