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diffusers
🤗 Diffusers: State-of-the-art diffusion models for image, video, and audio generation in PyTorch and FLAX.
In `diffusers` implementations (like InvokeAI) its pretty easy: https://github.com/huggingface/diffusers/blob/42beaf1d23b5cc...
But I also compile the VAE and some other modules, I will reply again later when I can look at my local code.
For the Automatic1111 repo (and presumably other original Stability AI implementations), I just add `m.model
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Judoscale
Save 47% on cloud hosting with autoscaling that just works. Judoscale integrates with Django, FastAPI, Celery, and RQ to make autoscaling easy and reliable. Save big, and say goodbye to request timeouts and backed-up task queues.
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= torch.compile(m.model)` here: https://github.com/AUTOMATIC1111/stable-diffusion-webui/blob...
I tried changing the options in the config dict one by one, but TBH nothing seems to make a significant difference.
I also havent messed with compiling LORA training yet, as I havent done it often as is sufficiently fast, but I'm sure it could be done.
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This is the master tracking list for MPS operator support: https://github.com/pytorch/pytorch/issues/77764
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detectron2
Detectron2 is a platform for object detection, segmentation and other visual recognition tasks.
I could fine-tune a Detectron2 model a few months ago using PyTorch and MPS backend [1]. I'd be interested if it's working yet.
https://github.com/facebookresearch/detectron2/issues/4342