Open models as checksum-verified magnet links. Censorship-resistant, kept alive by seeders.
149 comments
Orthogonalising activations at runtime is computationally cheap. Just distribute the refusal vectors (few thousand floats per layer), then run against the stock weights. Antirez's DS4 already supports this: https://github.com/antirez/ds4/blob/8db1d1d155cb0400a86a86b9...
Abliterated weights are just a bad habit we've gotten into. It's also deeply suboptimal from a precision point of view to take a model that's already been QATed and distributed in pre-quantised form (DeepSeek V4, Kimi K2.5 or K3...), modify its weights, and re-quantise it. Similarly, abliterated models regain some of their refusal behaviour when they're re-quantised after abliteration -- avoidable by keeping the two separate.
Such managed inference providers have (for now) plausible deniability of behaving ethically (at least enough that they don't get boycotted / scare away investors) due to them being "blind" to what gets run on their systems. They're acting as the inference equivalent of data transit carriers.
But I don't think it would be possible for managed inference providers to publicly expose "runtime activation steering" in the way antirez's DS4 does, without that reading much more explicitly as them inviting unethical workloads.
(Yes, there are other things you can do with runtime steering. But almost all of those things are workload-specific, relying on you privately tuning to the needs of your own dataset. And if you can do that, you can run inference without the help of a managed inference provider. The only time a customer will come along with a pre-made runtime-steering vector file in hand, is if that vector is an alignment-orthogonalization vector.)
Thanks for this information, Q4 seemed fine but they reappeared again in Q5 with an vengeance, I couldn't understand why. Very Strict and I've only found one jail break that barely works around 60% of the time.
I haven't wrapped my mind around this
There's an empirical observation that models often have a single direction in their activation space for "hmm no I shouldn't do this". It forms naturally during pre-training, and is then surfaced during post-training to make the model refuse to engage in certain behaviour.
With a little bit of linear algebra you can zap that direction from the model's activations, and it stops refusing to do things. You can also do the opposite: magnify that direction, and the model refuses to do anything at all.
As far as perennity is concerned it seems strictly better.
If this site represents a coordinated datahoarding effort then there will be at least a few people who will seed indefinitely.
EDIT/ Yes they did, that no longer seems to be the case though
When StarCraft 2 was lauched, the installer (before Battle.net installer crapware) had a complete graphical visualization of seeders & leechers.
Reference: https://warcraft.wiki.gg/wiki/Blizzard_Downloader
Once I was using Blizzard's downloader to install something (StarCraft, Diablo, I don't remember), and it was kinda slow. I disabled P2P downloads and speed skyrocketed, and I said "Huh, this was unexpected".
When P2P downloads disabled you could see the list of CDNs you're downloading from and mine had a single IP on that list. It looked familiar. Then it dawned on to me. It was the Akamai server which we were hosting in our system room, at 15 minutes of driving distance. After a chuckle, I went to get a cup of tea, because that was entertaining than the game itself.
Then of course, I dived into whatever I was installing that night.
Edit: From the screenshots in the wiki, I remembered that the progress bar was red. It was possibly Diablo 3, then. However, I'm still not 100% sure about it.
To get the file out to 100s or 1000s of machine they would often use private bittorent to distribute the file out.
It was very controversial. Users were angry that software companies were using their internet bandwidth to distribute their software. Made a lot of people angry.
If I understand the description correctly, microsoft still does this!
https://support.microsoft.com/en-us/windows/privacy/windows-...
Is hosting the same thing at 'academictorrents' actually a viable thing? In terms of peers from either send data to one another?
edit: looks like it can treat huggingface as a backstop for torrents that are otherwise not shared which is interesting, whole load of checksum nonsense I hand rolled disappear if bittorrent handles that. Except it doesn't work?
Magnet soon No seeders yet - a torrent mints once a seeder packages this model.
So there's some per-torrent work to be done, but I don't know what that is, and I don't see how it can be based on files I have locally _and also_ be an exact match to files on huggingface. So I'm missing something here.edit2: Looks like an implementation error. I can create a torrent from local files and upload it, but it won't have the huggingface backstop, and I can't specify it, so that doesn't actually achieve the claimed result. Before creating community torrents in that fashion would actually be of use, the submission page needs to allow pointing at the upstream.
Also, having everyone DIY a set of files -> torrent information is insane, this should not be a SKILLS.md, it should be a bash script that makes the thing.
Try asking it about Tianmen Square. I use DS myself, but let's not kid ourselves.
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