playbook/antigravity-awesome-skills/skills/huggingface-spaces/references/grants.md

Community GPU grants

When a non-PRO user has a good use case for ZeroGPU (open research demo, hobbyist project, educational tool, institutional showcase) and doesn't want to subscribe, they can request a free community grant from Hugging Face.

The flow

1. Build the Space. Create it as --flavor cpu-basic (the user is not PRO, so creating with --flavor zero-a10g will fail at create_repo). Code the app for ZeroGPU anyway — import spaces, @spaces.GPU, module-scope .to("cuda"). The Space will technically run on CPU until the grant is approved, but it'll be ready to switch over instantly.

   In this mode you can't iterate-with-real-inference before the grant — the CPU Space won't actually run heavy compute. Get the app to BUILD cleanly and RUNNING (even if the runtime would OOM on real input), then submit.

2. Submit a Community Tab discussion on the Space. Title:

   Apply for a GPU community grant: <Personal|Company|Academic> project
   

   Pick 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 "Non-PRO wants to build a public ZeroGPU app — happy to provide more context if helpful."

3. Wait. Open and publicly-facing applications by researchers, tinkerers, and institutions are typically approved. Approval can take days.

4. Once approved, the Space is moved to ZeroGPU automatically — no code change needed. The user comes back and you can iterate / refine with real GPU access.

When to suggest this

• User is not on PRO but their use case is a clear fit for ZeroGPU (a public ML demo, not a private tool).
• The model fits in large (≤ 48 GB VRAM at the chosen precision).

When NOT to suggest this

• Private / commercial / closed-source projects — push the user toward PRO instead.
• The model genuinely needs dedicated paid hardware (huge LLM, vLLM/JAX/ONNX as main model with heavy init) — canPay=True users can use paid flavors directly.
• The user is already PRO — they have ZeroGPU access; no grant needed.

Posting the request programmatically

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).