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@jacobtechtavern: Fun fact: You can use agents+CreateML to convert any model on HuggingFace into an iOS-compatible CoreML one, and make i…

X AI KOLs Timeline ↗ · 2026-11-02

Fun fact: you can use agents combined with CreateML to convert any HuggingFace model into an iOS-compatible CoreML model and make it roughly 3x faster.

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#coreml

I built an app to efficiently run decision models on the Apple Neural Engine with Shortcuts actions for OS automations

Reddit r/LocalLLaMA ↗ · 2026-10-19

Tinkerbox 是一个可将 LiquidAI d1-3B 等决策模型高效运行在 Apple Neural Engine 上的应用,支持通过 macOS Shortcuts 触发器实现无代码自动化,延迟低至约 40ms,并计划集成 vLLM/Qwen3.5 系列模型。

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#coreml

Laya (OS Jev) on Mac M4 CoreML Offline (45 decisions per second)

Hacker News Top ↗ · 2026-09-20

The Laya model runs offline on Apple's M4 chip using CoreML, achieving 45 decisions per second in inference.

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#coreml

iPhone Local TTS EPUB Reading - Audiobookify

Reddit r/LocalLLaMA ↗ · 2026-08-24

Audiobookify is an EPUB reader app for iPhone that features local offline TTS with optimized AI models for efficiency in battery life and narration quality.

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#coreml

@berryxia: Guys, I've done it! Fully open-sourced and free! I turned PP-OCRv6 directly into a local workstation, accelerated with CoreML on Mac, with one-click switching between Tiny, Small, and Medium model sizes! Tiny is only 1.5MB for extreme lightweight, Medium is 34.5MB for main...

X AI KOLs Timeline ↗ · 2026-06-17 Cached

The author turned PP-OCRv6 into a local workstation and open-sourced it for free, supporting Mac CoreML acceleration, providing three models: Tiny/Small/Medium, with image upload, batch processing, and multiple export formats, running locally to protect privacy.

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#coreml

iOS 27 Siri is using WaveRNN and FastSpeech2 [D]

Reddit r/MachineLearning ↗ · 2026-06-09

WaveRNN and FastSpeech2 models were discovered in the iOS 27 Simulator files, indicating their use for Siri's text-to-speech, alongside a logistic regression model for concert ranking.

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#coreml

Systematic Optimization of Real-Time Diffusion Model Inference on Apple M3 Ultra

arXiv cs.LG ↗ · 2026-05-19 Cached

This paper presents a systematic optimization study of real-time diffusion model inference on the Apple M3 Ultra, achieving 22.7 FPS at 512x512 resolution using CoreML conversion and a distillation model, revealing that CUDA-optimized techniques do not directly transfer to Apple's unified memory architecture.

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