Subchapter 19.9
references/grants.mdMarkdown3 KBView on GitHub
When a user has a good use case (open research demo, hobbyist project, educational tool, institutional showcase) and can’t pay for the hardware it needs, they can request a free community grant from Hugging Face.
Free personal accounts already get 2 ZeroGPU Spaces, so a grant is now for the cases that go past that:
Also bundled
READMEBuild the Space. If the user still has a free ZeroGPU slot, create it as --flavor zero-a10g and iterate normally with real inference before applying.
If they’re out of slots, create a Static Space instead (--space-sdk static — free for everyone) and push the app there; the SDK can be switched to gradio in the README frontmatter once the grant lands. Code the app for ZeroGPU anyway — import spaces, @spaces.GPU, module-scope .to("cuda"). In this mode you can’t iterate-with-real-inference before the grant, so just get the code in place and submit.
For a dedicated-GPU grant, get the app to BUILD cleanly and reach RUNNING (even if the runtime would OOM on real input), then submit.
Submit a Community Tab discussion on the Space. Title:
Apply for a GPU community grant: <Personal|Company|Academic> projectPick the closest fit. Body:
Description of the app: one paragraph on what it does + who it's for.
Justification: one paragraph on why this should run on ZeroGPU
(open-source, research, educational, etc.). If the user didn’t give you a justification, a reasonable default is “Public open-source demo, can’t cover the hardware cost — happy to provide more context if helpful.”
Wait. Open and publicly-facing applications by researchers, tinkerers, and institutions are typically approved. Approval can take days.
Once approved, the hardware is attached automatically — no code change needed (a Static holding Space still needs its sdk: flipped to gradio). The user comes back and you can iterate / refine with real GPU access.
large / 96 GB xlarge, or a non-PyTorch runtime — and the user can’t pay.canPay=True users who just need paid hardware — they can attach it directly.from huggingface_hub import HfApi
api = HfApi(token="hf_...")
api.create_discussion(
repo_id="<ns>/<space>",
repo_type="space",
title="Apply for a GPU community grant: Personal project",
description="<description and justification>",
)The Community Tab must be enabled on the Space (default — keep it on).