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senttoschool

macrumors 68030
Original poster
Nov 2, 2017
2,626
5,482
189539684-222482fb-63f7-4799-bfc1-005b84508e35.png
Stable Diffusion uses AI to generate images based on text: https://github.com/CompVis/stable-diffusion


Edit: One click installer available but with less features: https://github.com/divamgupta/diffusionbee-stable-diffusion-ui
 
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senttoschool

macrumors 68030
Original poster
Nov 2, 2017
2,626
5,482
One really cool thing about Apple Silicon is the unified memory. Normally, you need a GPU with 10GB+ VRAM to run Stable Diffusion.

But because of the unified memory, any AS Mac with 16GB of RAM will run it well. For example, an M1 Air with 16GB of RAM will run it.

However, to run Stable Difussion on a PC laptop well, you need buy a $4000 laptop with a 3080 Ti to get more than 10GB of VRAM.

I hope this trend continues and AS Macs become high valued machine learning inference/training computers.
 

eightace

macrumors newbie
Jan 7, 2012
21
3
This is great!
Using Dall-E already but will now be able to compare Stable Diffusion.
 

1096bimu

macrumors 6502
Nov 7, 2017
459
571
One really cool thing about Apple Silicon is the unified memory. Normally, you need a GPU with 10GB+ VRAM to run Stable Diffusion.

But because of the unified memory, any AS Mac with 16GB of RAM will run it well. For example, an M1 Air with 16GB of RAM will run it.

However, to run Stable Difussion on a PC laptop well, you need buy a $4000 laptop with a 3080 Ti to get more than 10GB of VRAM.

I hope this trend continues and AS Macs become high valued machine learning inference/training computers.
I have a desktop 2080ti with 11gb VRAM and I can't do anything larger than 512x512
unified memory makes so much sense, having a separate memory pool is so stupid. I wish the desktop PC market could move to SOCs rather than separate GPU and CPU.
 
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DaKKs

macrumors 6502
Aug 15, 2012
474
43
Stockholm, Sweden
Read about this and found it incredibly cool. Possibly stupid question however. According to the documentation 16GB is recommended but 8 gb "works". Does that mean its gonna swap my drive to hell or does it actually know when mac os says "hold on there buddy! I only got 8 gigs!"
 

innerproduct

macrumors regular
Jun 21, 2021
222
353
SD on M1 max 32 core will generate a standard output image in about 30s. On an nvidia 3090 GPU we are looking at 5 s or so. Would be really interesting so hear if the 64 core M1 Ultra is in the 15s or of this is another task where the ultra chip doesn't scale well.
 

Nermal

Moderator
Staff member
Dec 7, 2002
21,007
4,587
New Zealand
I just tried this out (a pain to get it all working, but that's beside the point). It seems that the rumours are true: Faces are the stuff of nightmares. Don't try to get it to make people if you want to sleep tonight! :)
 

Xiao_Xi

macrumors 68000
Oct 27, 2021
1,627
1,101
SD on M1 max 32 core will generate a standard output image in about 30s. On an nvidia 3090 GPU we are looking at 5 s or so. Would be really interesting so hear if the 64 core M1 Ultra is in the 15s or of this is another task where the ultra chip doesn't scale well.
Hopefully Apple can use this app as an internal benchmark to guide them in improving their GPU and Metal backend for Tensorflow and Pytorch.
 

mi7chy

macrumors G4
Oct 24, 2014
10,622
11,294
I just tried this out (a pain to get it all working, but that's beside the point). It seems that the rumours are true: Faces are the stuff of nightmares. Don't try to get it to make people if you want to sleep tonight! :)

Try increasing the sampling steps. If your installation is defaulting to 25, try 50 or higher. Just keep in mind output time increases.

1661440027115223.jpg
 

altaic

macrumors 6502a
Jan 26, 2004
711
484
Has anyone tried running Stable Diffusion with Tensorflow instead of Pytorch? Does it work faster?
I tried Diffusion Bee v0.3.0 (w/ tensorflow backend; M1 Max 10/32/64) and the performance was about the same as v0.1.0. Haven’t had the chance to try the repo you’re specifically asking about, though.
 

Xiao_Xi

macrumors 68000
Oct 27, 2021
1,627
1,101
I tried Diffusion Bee v0.3.0 (w/ tensorflow backend; M1 Max 10/32/64) and the performance was about the same as v0.1.0.
That's sad. I would have thought Stable Diffusion could run faster on Tensorflow because Apple has been working on the Metal backend for over a year.

Haven’t had the chance to try the repo you’re specifically asking about, though.
The dev of Stable Bee and the Stable Diffusion port to Tensorflow is the same, so Stable Bee should use that repo.
 

eas

macrumors regular
Oct 7, 2005
160
113
I've been using InvokeAI, which is a stable-diffusion fork. It can a 50 iteration 512x512 image in 60-80s on my M1 Pro MBP with 16GPU cores. I tried DiffusionBee a couple of weeks back and it was like 5x slower. I just tried DiffusionBee again now and it seems like it's taken a slight lead.

If you do try DiffusionBee, you should be aware that it plops the 4.5GB model in a hidden folder in your home directory. You'll want to delete that if/when you are done playing with the app.
 
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colinsky

macrumors regular
Apr 3, 2009
185
192
If you do try DiffusionBee, you should be aware that it plops the 4.5GB model in a hidden folder in your home directory. You'll want to delete that if/when you are done playing with the app.
Thanks, I was wondering where that extra 4.5GB was coming from.
 

VerizonLover

macrumors member
Apr 16, 2012
56
16
What features does one the one-click installer version not have that the brew version does?

Also 'python3 -V' doesn't give me the version number.
 
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