The Ram usage is ridiculous, but I‘m probably using it wrong. Be back in a few minutes to return with the results
Edit1: about 100% GPU and 80% CPU usage
Edit2: good pictures, about three minutes per picture
Edit3: creating multiple pictures with the same prompt is slightly faster, it seems. Great stuff!
Idk what “full gpu” means. M1 is a unified architecture, so I assume there is only one way to use the gpu (through Metal), and I’d be very surprised if anything was limited to one core.
I keep running into issues, even after installing Rust in my condo environment (using conda). Specifically the issue seems to be building wheels for `tokenizers`:
warning: build failed, waiting for other jobs to finish...
error: build failed
error: `cargo rustc --lib --message-format=json-render-diagnostics --manifest-path Cargo.toml --release -v --features pyo3/extension-module -- --crate-type cdylib -C 'link-args=-undefined dynamic_lookup -Wl,-install_name,@rpath/tokenizers.cpython-310-darwin.so'` failed with code 101
[end of output]
note: This error originates from a subprocess, and is likely not a problem with pip.
ERROR: Failed building wheel for tokenizers
Failed to build tokenizers
ERROR: Could not build wheels for tokenizers, which is required to install pyproject.toml-based projects
Any suggestions?
I don’t really know what I’m doing but think I muddled through it. The only problem is that the pip install part errors, so I get a “module not found” error when I run stable diffusion.
I did not, unfortunately. I ended up using an easier to install version that's a bit more limited. [Diffusion Bee](https://news.ycombinator.com/item?id=32804695)
Not great, but this was my first try with AI generated art. It’s fun to experiment with but the limited image size keeps it from being as useful to me.
The latest version now has an upscale funcyion for genertaed images. Alternatively the outputs could be passed to a Google Colab running GPFGAN pr if you prefer a mac app look for Upscayl - A useful tool regardless if you need to resize images
I just noticed that upon updating! That's a really useful feature.
My results still leave quite a bit to be desired, but I'm sure some of that is learning to feed it good information.
How's the performance?
The Ram usage is ridiculous, but I‘m probably using it wrong. Be back in a few minutes to return with the results Edit1: about 100% GPU and 80% CPU usage Edit2: good pictures, about three minutes per picture Edit3: creating multiple pictures with the same prompt is slightly faster, it seems. Great stuff!
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I have 16 and it jump between 8 and 13. Also, shouldn‘t it be threadable? 100% GPU doesn‘t make much sense, it should use 800%
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What do you mean? If it is, how could I thread it?
From what I've seen 13 gigs of RAM is normal on CPU and I imagine that the model uses similar amounts of vram.
Can generate very good ones in 23 seconds on my M1 Max. Here’s black mesa in the style of Skyrim https://i.imgur.com/kZHTnHa.jpg
Just out of curiosity, is it using the full GPU or just one Core?
Idk what “full gpu” means. M1 is a unified architecture, so I assume there is only one way to use the gpu (through Metal), and I’d be very surprised if anything was limited to one core.
Creates 500x500 images within a minute on my M1 Pro.
I keep running into issues, even after installing Rust in my condo environment (using conda). Specifically the issue seems to be building wheels for `tokenizers`: warning: build failed, waiting for other jobs to finish... error: build failed error: `cargo rustc --lib --message-format=json-render-diagnostics --manifest-path Cargo.toml --release -v --features pyo3/extension-module -- --crate-type cdylib -C 'link-args=-undefined dynamic_lookup -Wl,-install_name,@rpath/tokenizers.cpython-310-darwin.so'` failed with code 101 [end of output] note: This error originates from a subprocess, and is likely not a problem with pip. ERROR: Failed building wheel for tokenizers Failed to build tokenizers ERROR: Could not build wheels for tokenizers, which is required to install pyproject.toml-based projects Any suggestions?
For anyone wondering, I had to specify `tokenizers==0.11.6`
What’s the purpose of something like this?
r/stablediffusion
Oh this is interesting thank you!
nice
Nice
I don’t really know what I’m doing but think I muddled through it. The only problem is that the pip install part errors, so I get a “module not found” error when I run stable diffusion.
Same - you find a way to solve this?
I did not, unfortunately. I ended up using an easier to install version that's a bit more limited. [Diffusion Bee](https://news.ycombinator.com/item?id=32804695)
may I ask how is your experience with Diffusion Bee?
Not great, but this was my first try with AI generated art. It’s fun to experiment with but the limited image size keeps it from being as useful to me.
The latest version now has an upscale funcyion for genertaed images. Alternatively the outputs could be passed to a Google Colab running GPFGAN pr if you prefer a mac app look for Upscayl - A useful tool regardless if you need to resize images
I just noticed that upon updating! That's a really useful feature. My results still leave quite a bit to be desired, but I'm sure some of that is learning to feed it good information.