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Stable Diffusion 2.0 on Mac and Linux via imaginAIry Python library
- anothernewdude 4y ago2.0 is a mixed bag. It's set making pixel art back entirely. I'm pretty sure this is down to the aesthetic filter - it has a very biased idea of what good images are. It's silly to do that at the training stage, that should be something you do in the prompt. Fine tuning is out of reach for me, so I'm sticking to 1.5.
- bryced 4y agoTry out the pre-release like this: `pip install imaginairy==6.0.0a0 --upgrade` New 512x512 model supported with all samplers and inpainting New 768x768 model supported with the DDIM sampler only Not yet supported is the upscaling and depth maps. To be honest I'm not sure the new model produces better images but maybe they will release some improved models in the future now that they have the pipeline open.
- swyx 4y agocongrats! how did you upgrade it so fast? and what would you call out as the main technical pointers to adapting the base release for M1's?
- bryced 4y agoAll the same issues as migrating 1.5 to M1s. It went fast because I upgraded my existing codebase that had those fixes already instead of building of the new compvis one.
- deleted 4y ago[deleted]
- superpope99 4y agoThis seems to work for me. Incredible work turning this around so quickly!
- habibur 4y agoIf you are running it natively [ not on a cloud ] what's the ram size of your graphics card?
- yreg 4y agoAs with previous macOS Stable Diffusion tools, this is Apple Silicon only.
- smoldesu 4y agoIf you have an Intel Mac with sufficient memory, it's totally possible to run it on-CPU as well.
- dylan604 4y ago>If you have an Intel Mac with sufficient memory, which means what? why be so ambiguous. If if needs 16GB, say so. If it needs 32, say so. your sufficient memory comment is insufficient
- smoldesu 4y agoThe figure isn't static. Some models require as little as 3.5gb of free memory, others demand 8-16 gigs. MacOS is weird with memory management and everyone's Mac is different; I'd really only recommend running the model on 32-gig machines to avoid writing into swap, but technically it's possible with 8 and 16 gig machines.
- davely 4y agoI've been working on a web client[1] that interacts with a neat project called Stable Horde[2] to create a distributed cluster of GPUs that run Stable Diffusion. Just added support for SD 2.0: [1] https://tinybots.net/artbot?model=stable_diffusion_2.0 https://tinybots.net/artbot?model=stable_diffusion_2.0 [2] https://stablehorde.net/ https://stablehorde.net/
- davidkunz 4y agoWow, this a great site, thanks for the links!
- Smaug123 4y agoNicely done; this seems to work for me. In my own attempt, I got stock Stable Diffusion 2.0 "working" on M1 using the GPU but it's producing some of the most cursed (and low-res) images I've ever seen, so I've definitely got it wrong somewhere. The reader can infer the usual rant about dynamic typing causing runtime misconfiguration in Python.
- liuliu 4y agoThere are some network changes on the UNet, so if you ported the code over or have mismatched configuration files, it may generate garbage outputs, I wrote some notes here: https://www.reddit.com/r/StableDiffusion/comments/z42yph/some_notes_on_porting_sd2_over_to_iphone_or_other/ https://www.reddit.com/r/StableDiffusion/comments/z42yph/som...
- typest 4y agoHow much of this is stable diffusion 2, and how much is something else? For instance, the text based masks, the syntax like AND and OR, the face up scaling — are these all part of stable diffusion 2 (and can be used via other stable diffusion apis)?
- bryced 4y ago- text-based masks use a clipseg model. - the boolean mask logic is unique to this library - the face fixing is done by CodeFormer
- TekMol 4y agoWhat is a good VM to try this out? Something on AWS, Hetzner etc?
- petercooper 4y agoAWS g5.xlarge instances. Very fast (roughly RTX 3080 speeds) and about $1 an hour. However, you can just turn the instance on and off and not pay anything except the latent EBS cost.
- gbighin 4y agoRequirements: > A decent computer with either a CUDA supported graphics card or M1 processor. Why so? How does an M1 processor replace CUDA in a way a x86_64 processor can't? Do they use ARM assembly?
- pavlov 4y agoIt’s not the ARM core but the integrated GPU in the M1. It has access to the entire main memory unlike a traditional GPU with its own local VRAM.
- gbighin 4y agoOh, interesting! But does it support CUDA? How is the integrated GPU used for ML tasks?
- Filligree 4y agoIt does not support CUDA; SD does not require CUDA.
- pavlov 4y agoI believe there’s a Tensorflow acceleration adapter for Apple’s ML API which uses Metal behind the scenes.
- hnarayanan 4y agoBoth PyTorch and TensorFlow offer backends for Metal that works pretty well on Apple Silicon.
- dagmx 4y agoTo add to what people said, most of these ML models target an ML library like TensorFlow or PyTorch. Those in turn have hardware accelerated backends. Traditionally they’ve only had CUDA backends but Apple ported large chunks of both to Metal as well. So none of these libraries really target CUDA. In fact they’d run fine without a supported GPU but much slower.
- 4y ago
- 88stacks 4y agoawesome library, I haven't seen this before. I just added it to my stable diffusion api service so you can query stable diffusion 2.0 if you don't GPUs setup currently: https://88stacks.com https://88stacks.com
- fareesh 4y agoWhat's the minimum VRAM requirement?
- egeozcan 4y agoThis would have been perfect if it worked on Windows too. I need to look into dual booting Linux (opening a can of worms) just to give it a try, as WSL doesn't seem to cut it.
- boycott-israel 4y agofwiw dual booting is ultimately simpler than WSL and it's quirks
- bryced 4y agoIt might work on windows but I haven't tested it there.
- satvikpendem 4y agoWhy not use Automatic1111's? I think he already added SD 2.0.
- lostintangent 4y agoWow, this looks awesome! I noticed that the sample notebook doesn’t include SD 2.0 by default, and says that it’s too big for Colab. Is that a disk size/RAM limitation? As an aside, it would be cool if you versioned that notebook in the repo, so that it could be easily opened with Codespaces.
- bryced 4y agoYeah I tried to get it running but it kept crashing with "out-of-ram" errors. Good idea to version the notebook.
- algon33 4y agoNice, a friend was looking for something like this.
- greggh 4y agoThis is awesome, but I still like using the GUI for m1/m2 Macs, DiffusionBee. https://github.com/divamgupta/diffusionbee-stable-diffusion-ui https://github.com/divamgupta/diffusionbee-stable-diffusion-...
- malshe 4y agoThanks for sharing this. I was looking for something simple like this
- jibbers 4y agoAnd apparently Intel Macs also! I had no idea!
- diebeforei485 4y agoDoes this use Stable Diffusion 2.0?
- semicolon_storm 4y agoPretty slick, SD 2.0 performance actually seems to be better than 1.5?
- bryced 4y agoYou're probably noticing the newest sampler, which also works with 1.5.
- underlines 4y agois it possible to add volta or xformers for a massive speed increase? https://github.com/VoltaML/voltaML-fast-stable-diffusion https://github.com/VoltaML/voltaML-fast-stable-diffusion
- bryced 4y agoPossibly. Haven't tried. In principle should be possible.