I don't want to sound lazy, but I would be expecting a .dmg for Macs, and I don't seem to find it. Am I blind, or it simply hasn't been prepared yet?
Run Stable Diffusion on Your M1 Mac’s GPU
141–150 of 415 posts
Re: Run Stable Diffusion on Your M1 Mac’s GPU
#142Magnusviri[0], the original author of the SD M1 repo credited in this article, has merged his fork into the Lstein Stable Diffusion fork. You can now run the Lstein fork[1] with M1 as of a few hours ago. This adds a ton of functionality - GUI, Upscaling & Facial improvements, weighted subprompts etc. This has been a big undertaking over the last few days, and I highly recommend checking it out. See the mac m1 readme…
Nice. We'll get this guide updated for this fork. Everything's moving so fast it's hard to keep track! We struggled to get Conda working reliably for people, which it looks like lstein's fork recommends. I'll see if we can get it working with plain pip.
Running lstein's fork with these requirements[0] but seeing this output[1]. Same steps as original guide otherwise.
Anyone got any ideas?
[0] https://github.com/bfirsh/stable-diffusion/blob/392cda328a69...
[1] https://gist.github.com/bfirsh/594c50fd9b2e6b173e31de753a842...
Re: Run Stable Diffusion on Your M1 Mac’s GPU
#143Is there anyway to keep up with this stuff / beginners guide? I really want to play around with it but it's kinda confusing to me. I don't have an M1 Mac, I have an Intel one with an AMD GPU, not sure if i can run it? don't mind if it's a bit slow, or what is the best way of running it in the cloud? Anything that can product high res for free?
Yes, you can run it on your Intel CPU: https://github.com/bes-dev/stable_diffusion.openvino
And this should work on an AMD GPU (I haven't tried it, I only have NVIDIA): https://github.com/AshleyYakeley/stable-diffusion-rocm
There are also many ways to run it in the cloud (and even more coming every hour!) I think this one is the most popular: https://colab.research.google.com/github/altryne/sd-webui-co...
Re: Run Stable Diffusion on Your M1 Mac’s GPU
#144Earlier quoted context omitted.
Unscientifically that puts the M1 Pro GPU at about 25% of the performance of a RTX 3080. Not too shabby... EDIT - this comment implies it's much faster: https://news.ycombinator.com/item?id=32679518 If that's correct then it's close to matching my 3080 (mobile).
img2img runs in 6 seconds on my GeForce 3080 12 GB. 6+ it\s depending on how much GPU memory is available. If I have any electron apps running it slows down dramatically.
what args are you passing to img2img?
Re: Run Stable Diffusion on Your M1 Mac’s GPU
#145Is there a proper term to encapsulate M1/M2 Macs now that we have the M2? IE Apple Silicon Macs works but is a bit long. MX Macs? M-Series? ARM Macs?
The backend, as contributed by Apple is called MPS.
Re: Run Stable Diffusion on Your M1 Mac’s GPU
#146Anyone know the largest possible image size > 512x512? I'm getting the following error when trying 1024x1024 with 64 GB RAM on M1 MAX: /opt/homebrew/Cellar/python@3.10/3.10.6_2/Frameworks/Python.framework/Versions/3.10/lib/python3.10/multiprocessing/resource_tracker.py:224: UserWarning: resource_tracker: There appear to be 1 leaked semaphore objects to clean up at shutdown warnings.warn('resource_tracker: There appea…
I have the same problem with anything over 512x512 on my M1 Ultra with 128GB. VRAM must be capped.
Thanks for the Ultra data point.
I'm able to get 768x896 to run, but the output image is still white noisy at 50 ddim steps, perhaps related to the phenomena of being trained/windowed on 512x512 images as sibling squeaky-clean described.
RAM usage at various sizes: 512x512 14 GB, 768x768 26 GB, 768x896 32 GB
Re: Run Stable Diffusion on Your M1 Mac’s GPU
#147How large an image will this handle (versus how much RAM you have)? It seems the GPU memory requirements beyond 512x512 are obscene.
I'm on a iMac M1 16gb and I can handle up to 768x768 but since it's shared memory I close out every other application and run things overnight. The biggest issue with apple chips is that the --seed setting doesn't work. I should be able to set a seed to, for instance, 1083958 and if I re-run a command at the same resolution with that seed, I should get the same image every time. This would allow me to test different…
There's a partial fix for the seed issue on Reddit.
Re: Run Stable Diffusion on Your M1 Mac’s GPU
#148Is there a good set of benchmarks available for Stable Diffusion? I was able to run a custom Stable Diffusion build on a GCE A100 instance (~$1/hour) at around 1Mpix per 10 seconds. I.e, I could create a 512x512 image in 2.5 seconds with some batching optimizations. A consumer GPU like a 3090 runs at ~1Mpix per 20 seconds. I'm wondering what the price floor of stock art will be when someone can use https://lexica.art…
Related: I wrote up instructions for running Stable Diffusion on GCE. I used a Tesla T4, which is probably the cheapest that can handle the original code. If you're spinning up an instance to play with, rather than to batch-process, then cheaper makes more sense because most of the machine's time is spent waiting for you to type stuff and look at the results.
Re: Run Stable Diffusion on Your M1 Mac’s GPU
#149Earlier quoted context omitted.
Unscientifically that puts the M1 Pro GPU at about 25% of the performance of a RTX 3080. Not too shabby... EDIT - this comment implies it's much faster: https://news.ycombinator.com/item?id=32679518 If that's correct then it's close to matching my 3080 (mobile).
img2img runs in 6 seconds on my GeForce 3080 12 GB. 6+ it\s depending on how much GPU memory is available. If I have any electron apps running it slows down dramatically.
Curious about:
1. Image size
2. Steps
3. What your numbers are for text2img
4. (most importantly) are you including the 30 seconds or so it takes to load the model initially? i.e. if you were to run 10 prompts and then divide the total time by 10, what are your numbers?
Re: Run Stable Diffusion on Your M1 Mac’s GPU
#150This should be put into a docket image to avoid various potential conflicts with locally installed libraries. Anyone do this for the M1?
Do you want to add more layers to make it extra slow?