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Stable Diffusion 2.0

stability.ai

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Re: Stable Diffusion 2.0

#321

Post by IanCal »

minimaxir wrote: post #2

GitHub Repo: https://github.com/Stability-AI/stablediffusion HuggingFace Space (currently overloaded unsurprisingly): https://huggingface.co/spaces/stabilityai/stable-diffusion Doing a 2.0 release on a (US) 2-day holiday weekend is an interesting move. It seems a tad more difficult to set up the model than the previous version.

I think it's looking fairly similar, the first one was a bit tricky too. Later improvements by the community made it clearer.

The docs aren't good though, it tells you to download two things when actually I think you only need one. If you do need two then it doesn't tell you at all where to put the second.

You really need xformers if you're doing it at home, I've got a 3090 and it blew through the ram without it. However, the instructions didn't work for me for compiling and there's an incompatibility if you try and install from conda. You can have it work but you need to upgrade python from 3.8.5 to 3.9 in the yaml file first, then you can install it (xformers needs 3.9+, and something else in SD breaks on 3.10+ so 3.9 works).

This needs the classic "sit next to a new person installing it by following the docs and see what problems they hit, fix the docs and start from scratch again" process.

Looks good, though so far the images I've made don't look as nice as with 1.4, but I guess that's largely down to finding the right tweaks for the model and right magic wording for the prompts.

Re: Stable Diffusion 2.0

#322

Post by stavros »

It kind of annoys me that they removed NSFW images from the training set. Not because I want to generate porn (though some people do), but because I feel that they're foisting a puritan ethic on me. I don't consider the naked body inherently bad, and I don't like seeing new technology carry this (wrong, in my opinion) stigma.

Then again, it's their model, they can do whatever they want with it, but it still leaves me with a weird feeling.

Re: Stable Diffusion 2.0

#323

Post by edude03 »

wmwragg wrote: post #217
ftufek wrote: post #81

Earlier quoted context omitted.

To put things in perspective, the dataset it's trained on is ~240TB and Stability has over ~4000 Nvidia A100 (which is much faster than a 1080ti). Without those ingredients, you're highly unlikely to get a model that's worth using (it'll produce mostly useless outputs). That argument also makes little sense when you consider that the model is a couple gigabytes itself, it can't memorize 240TB of data, so it "learned"…

Well that would be ~4000 people each with an Nvidia A100 equivalent, or more with less, this would be an open effort after all. Something similar to folding@home could be used. Obviously the software for that would need to be written, but I don't think the idea is unlikely. The power of the commons shouldn't be underestimated.

Unlike folding@home the problem isn't very distributable because weights needs to be shared between GPUs via very high speed link

Re: Stable Diffusion 2.0

#324

Post by bonoboTP »

LunaSea wrote: post #320
bowsamic wrote: post #228

Earlier quoted context omitted.

No one is ever going to stop using all the available images until there is a law against it. Why would they?

There are already laws against it but enforcement is laking, as always.

If you can't process/digest copyrighted content with algorithms/machine learning then Google Search (the whole thing, not just Image Search) is dead.

So no, it's not at all clear where the legal lines are drawn. There have been no court cases yet, regarding the training of ML models. People are trying to draw analogies from other types of cases, but this has not been tried in court yet. And then the answer will likely differ based on country.

Re: Stable Diffusion 2.0

#325

Post by ajuc »

acadapter wrote: post #235
TaylorAlexander wrote: post #154

Earlier quoted context omitted.

Ah I am glad to see someone else talking about using public domain images! Honestly it baffles me that in all this discussion, I rarely see people discussing how to do this with appropriately licensed images. There are some pretty large datasets out there of public images, and doing so might even help encourage more people to contribute to open datasets. Also if the big ML companies HAD to use open images, they would…

Human artists derive their inspiration and styles from a large set of copyrighted works, but they are free to produce new art despite of that. Art would have developed much slower and be much poorer if, for example, Impressionism or Cubism had been entangled in long ownership confrontations in courts. Then there's the fact that humanity has been able to develop and share art and literary works for thousands of years…

> It would be interesting to see if this technology can erode the copyright concept a bit

Copyright law (especially in US) only ever changes in the direction that suits corporations. So - no.

What I expect instead is artists being sued by a big tech company for copyright violations because that big tech company used the artist Public Domain image for training their copyrighted AI and as a result it created a copyrighted copy of the original artist's image.

Re: Stable Diffusion 2.0

#326

Post by macrolime »

wmwragg wrote: post #217
ftufek wrote: post #81

Earlier quoted context omitted.

To put things in perspective, the dataset it's trained on is ~240TB and Stability has over ~4000 Nvidia A100 (which is much faster than a 1080ti). Without those ingredients, you're highly unlikely to get a model that's worth using (it'll produce mostly useless outputs). That argument also makes little sense when you consider that the model is a couple gigabytes itself, it can't memorize 240TB of data, so it "learned"…

Well that would be ~4000 people each with an Nvidia A100 equivalent, or more with less, this would be an open effort after all. Something similar to folding@home could be used. Obviously the software for that would need to be written, but I don't think the idea is unlikely. The power of the commons shouldn't be underestimated.

AFAIK. This is not possible at the moment and would need some breakthrough in training algorithms, the required bandwidth between the GPUs is much higher than internet speed.

Re: Stable Diffusion 2.0

#327

Post by [deleted] »

wokwokwok wrote: post #265
CamperBob2 wrote: post #211

Earlier quoted context omitted.

If I recompress 240TB as super low quality jpgs and manage to zip them up as single file that is significantly smaller than 240TB (because you can), does the fact they are not pixel perfect matches for the original images mean you’re not violating copyright? If you compress them down to two or three bytes each, which is what the process effectively does, then yes, I would argue that we stand to lose a LOT as a techno…

Maybe? Does that mean it’s worthless to try to train an ethical art model? Is it not helpful to show that you can train a model that can generate art without training it on copyrighted material? Maybe it’s good. Maybe not. Who cares if people waste their money doing it? Why do you care? It certainly feels awfully convenient for that there are no ethically trained models because it means no one can say “you should be…

[deleted]

Re: Stable Diffusion 2.0

#328

Post by bowsamic »

LunaSea wrote: post #320
bowsamic wrote: post #228

Earlier quoted context omitted.

No one is ever going to stop using all the available images until there is a law against it. Why would they?

There are already laws against it but enforcement is laking, as always.

No, it has not yet been demonstrated that the current copyright laws forbid the use of copyrighted images to train neural networks.

Re: Stable Diffusion 2.0

#329

Post by prakhar897 »

rob74 wrote: post #314
prakhar897 wrote: post #172

Earlier quoted context omitted.

I'm in a kind of same boat. I think indie games are the way to show true potential of SD. Hence, I'm working on http://diffudle.com/ which is a mix of Wheel Of Fortune + Stable Diffusion + Wordle. I Can't figure it out but feels to me like its lacking something.

Wow, that's really cool actually, have to bookmark it! One feature I would add would be going back through the previously shown images, that would make it easier to guess what they have in common. Also, larger images would look nicer, but I guess that would drive the costs up?

Thanks!! I'm debating whether to show history of images as it will reduce the difficulty by a lot. Larger images is a great suggestion, I'll add them ASAP.

Re: Stable Diffusion 2.0

#330

Post by prakhar897 »

Zitrax wrote: post #250
prakhar897 wrote: post #172

Earlier quoted context omitted.

I'm in a kind of same boat. I think indie games are the way to show true potential of SD. Hence, I'm working on http://diffudle.com/ which is a mix of Wheel Of Fortune + Stable Diffusion + Wordle. I Can't figure it out but feels to me like its lacking something.

It confused me that the letter boxes were divided in 7+3, thus I thought it would be two words while the correct answer was a single 10 letter word. Maybe try to avoid wrapping words.

Nice Observation!! I'm thinking including a start and end mark to improve the UX would work well. I can't avoid wrapping as the prompt might be very large.
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