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Stable Diffusion 2.0

stability.ai

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Re: Stable Diffusion 2.0

#391

Post by otabdeveloper4 »

FeepingCreature wrote: post #385
otabdeveloper4 wrote: post #382

Earlier quoted context omitted.

I fail to see the difference between "underlying structure" and "short-range visual features". Both are just simple statistical relationships between parameters and random variables.

Sure, but why would that not apply to humans? And we don't consider it copyright violation if a human learns painting by looking at art.

Depends on what you mean by "humans".

Most human behavior is easy to describe with only a few underlying parameters, but there are outlier behaviors where the number of parameters grows unboundedly.

("AI" hasn't even come close to modeling these outliers.)

Internet pictures squarely falls into the "few underlying parameters" bucket.

Re: Stable Diffusion 2.0

#392

Post by mdorazio »

prawn wrote: post #131

Hopefully related: If I'm a photographer wanting to improve resolution of my content for printing, what's my current best bet for upscaling? Is it realistic to make use of this on the command line, feeding it my own images? Or has someone wrapped it in an app or online service?

If you have a Nvidia GPU, I've been using Upscayl locally and for free with decent results: https://github.com/upscayl/upscayl

Note that on some image types it tends to make things look digitally painted rather than detailed. I recommend you try a few different tools and see what works best for the type of photography you do.

Re: Stable Diffusion 2.0

#393

Post by Duralias »

snowram wrote: post #344
jeroenhd wrote: post #266

Earlier quoted context omitted.

The main limitation for running these AIs is that you need tons of VRAM available for your GPU to get any good performance out of them. I don't have a video card with 12GiB of VRAM and I don't know anyone who does. If you're willing to wait more (30 seconds per image, assuming limited image sizes) there are repositories that will run the model on the CPU instead, leveraging your much cheaper RAM. In theory you could…

12GiB VRAM cards are common places nowadays. A RTX3060 is around ~450$ and available to everyone.

Unfortunately the 3060ti, 3070 and 3070ti are limited to 8GiB, so it is certainly not common.

In the price range it is the only Nvidia card with 12GiB and the 3080 starts at 10GiB.

So you can certainly get a 12GiB card without spending 3080+ money, but if you want any more power than a 3060 and keep the 12GiB then you would need to spring for a 3080 12GiB which is a big jump in price.

Re: Stable Diffusion 2.0

#394

Post by akie »

CuriouslyC wrote: post #387
in3d wrote: post #363

In addition to removing NSFW images from the training set, this 2.0 release apparently also removed commercial artist styles and celebrities [1]. While it should be possible to fine tune this model to create them anyway using DreamBooth or a similar approach, they clearly went for the safe route after taking some heat. 1. https://twitter.com/emostaque/status/1595731407095140352?s=4...

Removing NSFW content is fine, people who care about that can work around it easily. Removing celebrities and commercial artists was a mistake though and I expect this will need to be really impressive in other ways or people aren't going to bother using it.

It's remarkable, this sense of entitlement people have. You literally have a computer program here that can make photorealistic imagery of almost ANYTHING you ask it to, which was impossible even half a year ago, and here you are complaining that people won't use it unless it incorporates all of the protected imagery of famous artists and celebrities. Amazing.

Re: Stable Diffusion 2.0

#395

Post by [deleted] »

kmeisthax wrote: post #58

Is there a good explanation of how to train this from scratch with a custom dataset[0]? I've been looking around the documentation on Huggingface, but all I could find was either how to train unconditional U-Nets[1], or how to use the pretrained Stable Diffusion model to process image prompts (which I already know how to do). Writing a training loop for CLIP manually wound up with me banging against all sorts of stra…

[deleted]

Re: Stable Diffusion 2.0

#396

Post by layer8 »

LASR wrote: post #27

I am a solo dev working on a creative content creation app to leverage the latest developments in AI. Demoing even the v1 of stable diffusion to the non-technical general users blows them away completely. Now that v2 is here, it’s clear we’re not able to keep pace in developing products to take advantage of it. The general public still is blown away by autosuggest in mobile OS keyboards. Very few really know how far…

The dangerous thing is that people also don’t understand the limitations of that technology.

Re: Stable Diffusion 2.0

#397

Post by dismantlethesun »

akie wrote: post #394
CuriouslyC wrote: post #387

Earlier quoted context omitted.

Removing NSFW content is fine, people who care about that can work around it easily. Removing celebrities and commercial artists was a mistake though and I expect this will need to be really impressive in other ways or people aren't going to bother using it.

It's remarkable, this sense of entitlement people have. You literally have a computer program here that can make photorealistic imagery of almost ANYTHING you ask it to, which was impossible even half a year ago, and here you are complaining that people won't use it unless it incorporates all of the protected imagery of famous artists and celebrities. Amazing.

Is it entitled to think that a 2.0 will not have regressions on useful functionality?

Re: Stable Diffusion 2.0

#398

Post by ShamelessC »

choxi wrote: post #388
in3d wrote: post #363

In addition to removing NSFW images from the training set, this 2.0 release apparently also removed commercial artist styles and celebrities [1]. While it should be possible to fine tune this model to create them anyway using DreamBooth or a similar approach, they clearly went for the safe route after taking some heat. 1. https://twitter.com/emostaque/status/1595731407095140352?s=4...

Mixing artist names was by far the most effective way to create aesthetically pleasing images, this is a huge change. DreamBooth can only fine-tune on a couple dozen images, and you can't train multiple new concepts in one model, but maybe someone will do a regular fine-tune or train a new model.

I'd be curious how well the model still performs given such prompts. Disparate concepts, interpolation, n' all that. Surely it performs worse - but I bet it gets closer than you might think.

Re: Stable Diffusion 2.0

#399

Post by machina_ex_deus »

in3d wrote: post #363

In addition to removing NSFW images from the training set, this 2.0 release apparently also removed commercial artist styles and celebrities [1]. While it should be possible to fine tune this model to create them anyway using DreamBooth or a similar approach, they clearly went for the safe route after taking some heat. 1. https://twitter.com/emostaque/status/1595731407095140352?s=4...

I predicted back when they started backpedaling that there's a chance that sd1.4 or 1.5 will be the best available model to the general public, for a very long duration, because the backlash will force them to self-castrate themselves.

You can see nobody likes this new model in any of the stable diffusion communities. It's a big flop and for a good reason. The reason it was so successful in the first place was because you could combine artist names to get the model to the outcome you want.

I'll again remind anyone who thinks they might want to use this to download a working version of SD now. They might break their own libraries in the future, and getting SD1.4 could be a real hassle in a year or so. Getting the right .ckpt file, which can have pickled python malware, is not so trivial, and this will get worse in time.

It's going to diverge into castrated official model that intentionally breaks the older models and older models from unofficial shady sources that might contain malware.

Re: Stable Diffusion 2.0

#400

Post by ShamelessC »

jimmySixDOF wrote: post #247
ShamelessC wrote: post #93

Earlier quoted context omitted.

> Writing a training loop for CLIP manually wound up with me banging against all sorts of strange roadblocks and missing bits of documentation, and I still don't have it working. There is working training code for openCLIP https://github.com/mlfoundations/open_clip But training multi-modal text-to-image models is still a _very_ new thing, in terms of the software world. Given that, my experience has been that it's ne…

All this horsepower deployed to image generation is interesting but somebody wake me up when there is a stable diffusion for SQL or when on demand generative User Interfaces are spun up on the fly to suit the purpose.

Will do!
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