Stable diffusion per Apple Silicon ufficiale da Apple

Today, we are excited to release optimizations to Core ML for Stable Diffusion in macOS 13.1 and iOS 16.2, along with code to get started with deploying to Apple Silicon devices.
Rif e commenti su hacker news

Di seguito il link al progetto Github:

Stable Diffusion with Core ML on Apple Silicon
https://github.com/apple/ml-stable-diffusion
221 forks.
5,165 stars.
79 open issues.

Recent commits:

Image2image – python (#115)* Add Encoder model to torch2coreml for image2imageand later for in-paining* diagonal test with randn* Revert "diagonal test with randn"This reverts commit 270afe1bb970c9413d3c3c9d09c0bd4f2dcbfa19.* readme updates for encoder* pr comments, GitHub
Update import to nested path (#109)* Update import to nested path* Update python_coreml_stable_diffusion/unet.pyCo-authored-by: Pedro Cuenca <pedro@huggingface.co>Co-authored-by: Atila Orhon <64497909+atiorh@users.noreply.github.com>Co-authored-by: Pedro Cuenca <pedro@huggingface.co>, GitHub
Fix downsample channels. (#110)Reference: https://github.com/huggingface/diffusers/blob/main/src/diffusers/models/unet_2d_blocks.py#L749-L756This is usually not a problem for Stable Diffusion models. However, somearchitectures such ashttps://huggingface.co/OFA-Sys/small-stable-diffusion-v0 wouldn'tconvert., GitHub
Add guidance scale flag for python CLI (#95), GitHub
Make `negativePrompt` optional in Swift CLI (#89), GitHub

Di Stable Diffusion, un software di machine leraning, per creare immagini da descrizioni testuali in inglese, abbiamo parlato diffusamente in questo articolo

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Stable diffusion per Apple Silicon ufficiale da Apple

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