Torrents should really be the preferred method for distributing AI model weights. Why rely on a single point of failure like Hugging Face? BitTorrent was made for exactly this.
In my experience public torrents often die as they grow older. It doesn't help that BitTorrent V1 makes long term seeding annoying, and BitTorrent V2 is almost never used.
I never understood this, is there anything that makes it difficult for the original uploader, the one that supposedly offers the file directly, to offer a torrent instead for the same amount of time?
As far as perennity is concerned it seems strictly better.
Every change to the source is effectively a new torrent. This creates a ton of fragmentation as data is reorganized, remixed, reencoded, and so on.
You can see this with many Linux distros: there is no single Debian torrent that people seed for years because there's always a refreshed version.
Distros are a bad use case for P2P anyway since you depend on upstream as soon as you start upgrading and installing packages.
You can trivially have storage deduplication for the files served via torrent, transparent to the protocol. The most trivial version of this that you can do today with pretty much any client is having a single directory containing files serving multiple overlapping torrents.
I don't see why it would be. It's transparent to other clients just like it is to the protocol. It cannot be more complex than alternatives by construction.
phoyd · · focus · HN ↗
CodesInChaos · · focus · HN ↗
monsieurbanana · · focus · HN ↗
As far as perennity is concerned it seems strictly better.
zenoprax · · focus · HN ↗
You can see this with many Linux distros: there is no single Debian torrent that people seed for years because there's always a refreshed version.
Distros are a bad use case for P2P anyway since you depend on upstream as soon as you start upgrading and installing packages.
chmod775 · · focus · HN ↗
skeledrew · · focus · HN ↗
This sounds wildly complex, especially from a discovery perspective.
chmod775 · · focus · HN ↗
deadbunny · · focus · HN ↗