Any-Winter-4079

I'm running dev + https://github.com/invoke-ai/InvokeAI/pull/1243 w/ 64GB + MacOS Monterrey and I can run it.

> assertion `[MPSNDArray initWithDevice:descriptor:] Error: total bytes of NDArray > 2**32' I would've sworn it was 2^31 before. I guess there's some metal changes. Edit. Yeah, see `Error: product of...

@i3oc9i @pauloportella In general for a temporary fix, I'd check attention.py and model.py (I think) and simply ensure the tensors are not >2^32 Specifically here, for the `slice_size`(s)

Thinking about it, you could do a PR where you check the OS version, and then use a different slice size. ``` import platform platform.platform() ``` `'macOS-12.5.1-arm64-arm-64bit'`

Do you guys get ``` ERROR: Could not find a version that satisfies the requirement triton==2.0.0.dev20220701 (from versions: 0.1, 0.1.1, 0.1.2, 0.1.3, 0.2.0, 0.2.1, 0.2.2, 0.2.3, 0.3.0) ERROR: No matching...

@lkewis I got Textual Inversion to work on M1 thanks to your guide, after fixing the `nan` M1 error. Have you done any more experiments? It'd be good to create...

Awesome! I tried using Dreambooth but it was climbing beyond 120GB RAM (well, half swap) on my M1. I'll check out the new update. As for regular Textual Inversion, `num_vectors_per_token:...

Oh, yeah, absolutely. I just took a screenshot from the Reddit post, to try to replicate your results. I'll remove the training images from the PR (and from #517), since...

@lkewis I've removed the images on the zip from the Pull Request https://github.com/invoke-ai/InvokeAI/pull/814 and deleted a Reddit post I had just created, documenting the result (without training images, but still,...

Dreambooth is one of the things I really want to get to work on M1. I've tried learning from selfies of myself with regular Textual Inversion and results were meh....