Search Results for "m1"

Don't let cumbersome web debugging tools hold you back. With Proxyman's native macOS app, you can capture, inspect, and manipulate HTTP(s) traffic with ease. Intuitive, thoughtful, built with meticulous attention to detail. Comprehensive Guideline to set up with iOS simulator and iOS and Android devices. Proxyman acts as a man-in-the-middle server that capture the traffic between your applications and SSL Web Server. With built-in macOS setup, so you can inspect your HTTP/HTTPS Request and...

SignTools is a sideloading platform that takes a different approach from any similar tools. It consists of two components — a service and a builder. The builder is a macOS machine which performs signing using official Apple software. Doing so means high reliability and compatibility. The service (this repo) can be hosted anywhere, and it provides a web interface for you to upload, sign, and download apps, using the builder where necessary. Having the web service means that you don't need...

...Android import hook, thanks to xHook. iOS fishhook and substrate and whale hook. unicorn backend support simple console debugger, gdb stub, instruction trace, memory read/write trace. Support iOS objc and swift runtime. Support dynarmic fast backend. Support Apple M1 hypervisor, the fastest ARM64 backend. Support Linux KVM backend with Raspberry Pi B4.

ANE Transformers is a reference PyTorch implementation of Transformer components optimized for Apple Neural Engine on devices with A14 or newer and on Macs with M1 or newer chips. It demonstrates how to structure attention and related layers to achieve substantial speedups and lower peak memory compared to baseline implementations when deployed to ANE. The repository targets practitioners who want to keep familiar PyTorch modeling while preparing models for Core ML/ANE execution paths. Documentation highlights reported improvements in throughput and memory residency, while releases track incremental fixes and packaging updates. ...

...In this repository, I will code along with the book Programming with 64-Bit ARM Assembly Language, adjusting all sample code for Apple's ARM64 line of computers. While Apple's marketing material seems to avoid a name for the platform and talks only about the M1 processor, the developer documentation uses the term "Apple Silicon". You need Xcode 12.2 or later, and to make things easier, the command line tools should be installed. This ensures that the tools are found in default locations. All application samples also require at least macOS Big Sur, iOS 14 or their respective watchOS or tvOS equivalents. ...

This repository provided a pre-release of TensorFlow and TensorFlow Addons tailored for macOS 11+ with native hardware acceleration via Apple’s ML Compute, supporting both Apple Silicon (M1) and Intel Macs. It shipped ready-made Python 3.8 wheels and install scripts so developers could quickly get an accelerated stack running without building from source. As TensorFlow added a Metal PluggableDevice path, the project directed users toward using Apple’s tensorflow-metal to get GPU acceleration on Mac directly through Metal. ...

...No configuration or maintenance needed. The source code is available on GitHub under the permissive MIT license. Hush is written in Apple's latest programming paradigm Swift UI and has native support for M1 processors. The app download clocks in at less than half a megabyte.