Publish, then improve: routing around the 20-Space cap
The night my pipeline finally had a large batch ready to ship, Hugging Face returned this:
429 Too Many Requests
You have exceeded the rate limit for space creation (20 per day).
You can retry this action in 1 day.
Twenty new Spaces per rolling 24 hours, per account. I had 19 creations already inside the window and a queue holding roughly 57 points of gate-approved papers. And no, a paid account does not lift it: my account is Pro, and the ceiling did not move. Pro raises quotas, the resources you may consume. This is a rate limit, an anti-abuse control on how fast repositories can be created, and it applies to every tier. Learning the difference cost me one confused evening.
The asymmetry that saves the strategy
The cap meters exactly one operation: creating a new Space. Updating an existing Space is uncapped. Meanwhile the official judge re-scores a submission whenever its content changes. Put those two facts together and the constraint inverts into a strategy:
A Space is a slot you buy once. Evidence is a payload you can upgrade forever.
So the workflow stopped treating publication as the finish line. Publish early, even imperfect, to claim the slot and get a baseline verdict. Then improve the evidence and push updates in place. Every update triggers a fresh judging at zero cap cost. The score climbs without spending a single creation. In multi-objective terms each in-place update is a free Pareto improvement: the score goes up and no constrained axis, whether dollars, publish slots, or time, moves against it, which is the only kind of move you never have to think twice about.
One night of in-place upgrades
The receipts, all on already-published Spaces, all without touching the cap:
- A theory paper at 0 of 10 got a genuine executed experiment suite and re-scored at 4.
- A mechanism-design paper at 3 of 10 got the authors' own release driven across a parameter sweep and re-scored at 6.
- An auction paper at 1 of 12 got the authors' C++ compiled and run on the shipped dataset and re-scored at 5.
- An uncertainty-quantification paper regressed from 3 to 0 when my rewrite mismatched the judge's claim set, then recovered once the missing dataset run was added. Same mechanism in both directions: the judge re-scores what changed, including your mistakes.
Combined, five papers went from 8 official points to 19 in one night of updates, eleven points of pure movement up the score axis at zero cost on the capped one, while the 57-point queue of new papers waited for the window to roll.
Compounded over the campaign, that habit is most of the standing. As of July 28 the account sits 14th of 238 entrants on 624 points across 99 judged papers, and a large share of those points came from Spaces that were already published and simply got better evidence.
The mechanics worth stealing
Re-sync like you mean it. An in-place update is only safe if what lands remotely is exactly what passed the local gates. The protocol: stage the update privately, download the remote pages and verify their digest matches the local gate digest byte for byte, re-activate the challenge tags, then flip public. If the digests differ, something edited in transit, and the publish aborts.
Deletions need their own step. The publishing tool only adds and updates files. A page deleted locally stays alive remotely, and the stale page changes the remote digest, which blocks the sync. Removing a page means an explicit remote folder deletion. This one cost me a failed re-sync before I understood it.
Drain the queue on a timer. The rolling window frees slots as old creations age out, and it does so on the platform's schedule rather than mine. An hourly retry attempts the queued creations, publishes whatever fits, skips what is already live, treats the 429 as an expected outcome rather than an error, and deletes itself when the queue is empty. Backpressure handled, no human refreshing a dashboard at 2 a.m.
What transfers
- Read the error before designing around it. Rate limit and quota are different animals, and money only fixes one of them.
- Find the uncapped operation adjacent to the capped one. Creation was metered; mutation was free. Most platforms have a pair like this.
- If your evaluator re-scores on change, iteration in place is a scoring engine. Ship the slot early and let updates do the climbing.
- Verify remote state against local truth before going public. Digest comparison turned risky hot-updates into a safe routine.
- Let a dumb retry loop absorb the platform's schedule. The window rolls whether or not you are watching.