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Stable Diffusion 2.0

stability.ai

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Re: Stable Diffusion 2.0

#431

Post by choxi »

ShamelessC wrote: post #398
choxi wrote: post #388

Earlier quoted context omitted.

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.

Here’s a comparison study on Reddit: https://www.reddit.com/r/StableDiffusion/comments/z3ferx/xy_...

It does look like artist names have a significantly reduced effect.

Re: Stable Diffusion 2.0

#433

Post by magic_at_nodai »

tormeh wrote: post #360

I can't see any progress on AMD/Intel GPU support :( Would love to see Vulkan or at least ROCm support. With SD1 you could follow some guides online to make it work, since PyTorch itself supports ROCm, but the state of non-Nvidia GPU support in the DL space is quite sad.

Try SHARK on your AMD GPUs for SD. Follow the setup here: https://github.com/nod-ai/SHARK/tree/main/shark/examples/sha....

It works with Pytorch -> torch-mlir -> MLIR / IREE -> vulkan. Works on both Windows and Linux. And has a simple gradio web UI https://github.com/nod-ai/SHARK/tree/main/web but we plan to enable better UI integrations very soon.

Join us on discord https://discord.gg/RUqY2h2s9u if you have any trouble. Appreciate any / all feedback.

Re: Stable Diffusion 2.0

#434

Post by blihp »

Existenceblinks wrote: post #297
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 wonder why these AI repos' documentation are so bad compared to what we are used to in general. Where is intro/get started/example(commands)/config(docs) etc.

I believe it's a combination of the fact that most of these models are basically 'research dumps' primarily targeting other researchers and given this they are assuming a level of familiarity with related tools/libraries. So it's up to interested people in the community to take it the last mile/block/whatever to make it easy to use, address specific use cases etc. for use by a less academic/technical audience.

Re: Stable Diffusion 2.0

#436

Post by LunaSea »

bowsamic wrote: post #328
LunaSea wrote: post #320

Earlier quoted context omitted.

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.

The moment you make money from it the law is pretty clear.

Re: Stable Diffusion 2.0

#437

Post by beernet »

stavros wrote: post #322

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…

Agreed. I could see this being driven by EleutherAI in the background who are very, say, strict when it comes to "alignment".

Re: Stable Diffusion 2.0

#439

Post by hfbff »

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.

I don't think you're using the principle of charity here ("make the best interpretation of a post"). The person isn't complain, he/she is just saying that people will probably return to v1 unless v2 has something impressive to compensate.

Re: Stable Diffusion 2.0

#440

Post by Applejinx »

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.

That really depends on whether you mean 'like artist X' as 'aesthetically pleasing'. I was fooling around with furry diffusion and got to try a few different models. Yiffy understood artist names, and furry did not: it had further training but stripped of artist tags.

All these models are pretty good as that community is strong on art, styles, art skill, and tagging, causing the models to be a serious test case for what's possible. The model with artist names was indeed capable of invoking their styles (for instance, an artist with exceptional anatomy rendering had it translate into the AI version). The more-trained model without the artist names was much more intelligent. It was simply more capable of quality output, so long as your intention wasn't 'remind me of this artist'.

I think that's likely to be true in the general case, too. This tech is destined for artist/writer/creator enhancement, so it needs to get smarter at divining INTENT, not just blindly generating 'knock-offs' with little guidance.

What you want is better tagging in the dataset, and more personalized. If I have a particular notion of an 'angry sky', this tech should be able to deliver that unfailingly, in any context I like. Greg Rutkowski not required or invoked :)

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