#Could InvokeAI be run on Colab or RunPod
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We do have a Colab notebook, but I don't know if it's up-to-date, and it's not really supported (the contributor hasn't been around in a while) https://github.com/invoke-ai/InvokeAI/blob/main/notebooks/Stable_Diffusion_AI_Notebook.ipynb
@worldly rose https://runpod.io/gsc?template=vm19ukkycf&ref=mk65wpsa
Thank you @candid turtle i keep meaning to try it!
Hi, everyone! Can anyone tell me if the notebook is updated?
unfortunately Colab doesn't support python3.9, which is our minimal requirement. otherwise there's really no reason you couldn't run Invoke on Colab. we're just waiting on Google to get their act together.
Even if WE install python 3.9 on the terminal of colab ?
good question, I haven't tried it in the terminal (i tried to script it in the notebook itself, and it exploded miserably). If there's a way to get Colab to use a 3.9 kernel, there's no reason why Invoke wouldn't run there. we'd also need some way to expose the UI to the internet, like ngrok or something
Ever wanted to try invoke ai's awesome stable diffusion infinite canvas out, but didn't want to go through the hassle of installing a bunch of stuff? Maybe you just don't have a local GPU that can run it fast enough? No worries, we've got you covered with our easy deploy template for invoke ai!
@brisk shadow our Runpod template is much improved from the last time you saw it (no need to stop and restart the pod anymore) and uses a lightweight, up-to-date image! give it a try π https://runpod.io/gsc?template=vm19ukkycf&ref=mk65wpsa
someone asked me for the latest and I was confused what version it was on lol
I'm like uhhhh I have no idea and have no idea how to find out π
yea, the :development image you originally used as the base hasn't been maintained
thanks for your work on Runpod btw. π
yeah this looks much better - my only feedback would be that it looks like it would have to download the sd1.5+inpainting model for every unique user. We actually cache them via the docker image so that subsequent users can start invoking in about 20s
this wasn't too bad, started in about 4m
yeah that's fair. but baking the runtime dir into the image balloons it to 18GB :(... I wonder if there's some shared model cache we can pull from when running on Runpod? so it's more local than just pulling from HF.
also, this way I think it's more flexible for the user - they can manage their runtime dir with custom models, etc. and with our upcoming move to diffusers, the model dir structure might change, so a "baked" image might break
awesome, looking forward to that!
ah yeah, I heard you were going to make model management easier