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.
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Di seguito il link al progetto Github:

Stable Diffusion with Core ML on Apple Silicon
https://github.com/apple/ml-stable-diffusion
892 forks.
16,522 stars.
168 open issues.

Recent commits:

Add SD3 Pipeline (#329)* Add SD3 PipelineCo-authored-by: atiorh <atiorh@users.noreply.github.com>Co-authored-by: arda-argmax <arda-argmax@users.noreply.github.com>* Use swift-transformers for tokenization* Use diffusionkit converters in torch2coreml* Documentation and cleanup* Add model link* Consolidate batch prediction logic* Remove DecoderSD3.swift and consolidate logic into Decoder.swift* Remove DiffusionKit MLX inference reference from README———Co-authored-by: atiorh <atiorh@users.noreply.github.com>Co-authored-by: arda-argmax <arda-argmax@users.noreply.github.com>Co-authored-by: atila <atiorh@icloud.com>, GitHub
Update pull_request_template.md after changing to MIT license, GitHub
Update CONTRIBUTING.md to reflect the MIT license, GitHub
Update LICENSE.md to MITChanging repository license to MIT, GitHub
Update swift-argument-parser to latest minor versionThis will also make ml-stable-diffusion more tolerant with regard to which swift-argument-parser version it needs, resulting in fewer version conflicts in Xcode projects., Alejandro Isaza

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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