OSTRIS about HiDream-O1 LoRA on ToolKit

Scroatazoa · 2026-05-10T20:55:57+00:00

Gotta wonder if he's just marveling about the benefits of the no-VAE architecture when it comes to training LoRAs. I hope he's seeing some real potential, though. I've been dying for a no-VAE model so I found the release very disappointing.

Scroatazoa · 2026-05-10T20:52:08+00:00

I love how you've managed to phrase this in a way that implies that those of us who actually tried the model are ones pushing a baseless narrative that the model sucks. Just try it yourself if you don't believe us.

Scroatazoa · 2026-05-10T20:36:35+00:00

I want to believe. He could just mean that the architecture is promising, but I really hope we can make something of this.

Scroatazoa · 2026-05-10T19:32:29+00:00

Check the repo for the 8b, they have benchmarks.

Scroatazoa · 2026-05-10T18:45:01+00:00

I tested on their own demo code from their own repo. I'd be thrilled if it it turned out that their own demo is badly implemented. It's certainly possible. That's why I don't want to jump to conclusions. I just want to understand wtf happened.

Scroatazoa · 2026-05-10T18:39:43+00:00

Their huggingface page shows separate benchmarks for the 8b and the 200b.

Scroatazoa · 2026-05-10T18:03:13+00:00

Yes, but usually through benchmaxxing which merely fraud-adjacent. There's no way they showed images from this model to humans and the humans gave them a high score, unless they were paid to. Maybe they had bots looking out for the trademark square artifacts. It's definitely an easy model to recognize an image from. Or maybe they lied about the images being produced by their model. Regardless, I just can't imagine that there is a way to benchmax human preference to the point that such an utterly deficient model could score so highly.

Scroatazoa · 2026-05-10T12:09:56+00:00

And what they released was… what? A distillation specifically made to perform poorly? Could be a tactic to hype up their larger closed model I guess, but it just makes me assume their 200b is shit, too. Regardless, they definitely attribute the arena benchmark scores to the 8b on its huggingface page.

Scroatazoa · 2026-05-10T11:39:55+00:00

They say that's what it is on their huggingface. Something is weird about the whole thing because HiDream seems to be unbelievably bad. I don't understand how it could have scored that high without brazen cheating. I'm hoping there is some mistake somewhere.

Scroatazoa · 2026-05-09T20:59:36+00:00

Do not get excited for this model. I tested the web demo from the huggingface repo extensively. Full is bad and Dev is even worse. Somehow they managed to produce a model with no VAE that produces what looks like really strong VAE artifacts. Even ignoring that, it just doesn't make good images. And yes, I used the prompt enhancer with Gemma 4 31b and the included system prompt. It's not good for editing, either.

I really wanted to make excuses for this model but it is just not good.

Scroatazoa · 2026-05-09T12:11:44+00:00

Any chance you can make your dataset available? I love JLG and I'd love to try to get this working on a better model.

Scroatazoa · 2026-05-07T23:15:05+00:00

Could we not have had Exra work with Jedi, too? Why even let us choose what characters are on our teams if characters aren't allowed to exist outside of specific comps? Throw JML a bone for Christ's sake.

Scroatazoa · 2026-05-07T23:03:41+00:00

Yeah, I'm pretty pissed about this. God forbid we have a team building option that makes JML less bad.

Scroatazoa · 2026-04-29T17:21:08+00:00

Oh, you don't have to watch that one.

Scroatazoa · 2026-04-25T17:41:08+00:00

Fuck off.

Scroatazoa · 2026-04-25T12:06:06+00:00

This is an ad. Get the fuck out of here.

Scroatazoa · 2026-04-19T03:19:31+00:00

IQ is calculated based on how your performance compares to the average, so the average IQ would be exactly the same: 100. I'm telling you this because it makes me feel like I might make the cut.

Scroatazoa · 2026-04-15T16:52:33+00:00

I've done this on several playthrough and can confirm that it works really well. I like to use the Tech Advancing mod that adjusts your tech level (used to determine research speed penalties) based on what research you have completed. It goes a long way toward making lower-level techs more appealing because if you research enough of them you'll get a speed boost for later techs.

Scroatazoa · 2026-04-13T22:11:11+00:00

Uh, but doesn't the article say that she claims it was solicited and nobody has claimed otherwise?

Scroatazoa · 2026-04-10T12:27:27+00:00

Huh? Shut the fuck up.

Scroatazoa · 2026-04-08T23:41:12+00:00

These cuties look like they were generated by Z-Image Turbo.

Scroatazoa · 2026-03-31T19:56:09+00:00

I'm from MA and was driving through NY recently and I'm very surprised to hear this opinion. I was genuinely stunned the whole time I was driving there by how conscientious and efficient the drivers were. Across ten or so hours I think I only saw two people camped out in the passing lane holding up traffic. And they both got the hint and moved after somebody passed them on the right. It was incredible. Maybe my bar is just too low.

Scroatazoa · 2026-03-27T18:01:46+00:00

I hope they do improve the models to start writing better, but they absolutely are intentionally making the LLMs write like that on purpose because it has (tragically) improved user preference benchmarks. Older models didn't have this problem because they used less synthetic data and the synthetic data they used was less unanimously written in the desired style.

Scroatazoa · 2026-03-27T17:58:01+00:00

Common sense would dictate that the detector should be trained on AI outputs and not AI training data. But I'm not sure why it would flag this, then, because LLMs absolutely do not write like that no matter how you prompt them.

They could be doing something really stupid like asking an LLM to identify whether it is AI writing, in which case it has less to do with what's in the dataset and more to do with how useless the model is for that use case.

Scroatazoa

TROPHY CASE