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ai-agent

ml-macos-performance: Boost AI

Get improved AI performance on macOS with ml-macos-performance, a Swift tool for founders.
intermediateโฑ 1-2 hours๐Ÿ’ต Free
100 stars6 forksSwiftQuality 8/10Updated 6/5/2023100% free ยท open source
What it is

Use the Swift tool to boost AI performance on macOS.

What you can make with it

Apps and experiences with improved performance on macOS, like a data-intensive game or a high-performance machine learning model.

How it helps

It helps by optimizing AI performance on macOS, so you can run demanding AI applications with better speed and reliability.

Real use case example

"A founder needs to build a fast AI-driven recommendation engine for their e-commerce platform. They create the engine using this tool, integrate it with their existing macOS infrastructure, and after 2 hours of setup, the engine is up and running, delivering accurate product suggestions to their customers."

If you're new

Beginners can start with this when they need to quickly prototype and test AI-driven projects on macOS.

If you're senior

Senior engineers and developers will reach for this when they need to optimize AI performance on macOS for demanding applications.

Common confusion cleared up

This tool doesn't replace a native macOS AI framework, but rather serves as a Swift-based library to improve performance on macOS.

Best inside these AI tools
Codex CLIContinueAny AI Client
Pairs with
Stripe webhookNotion databaseClaude API
Why we list it on WorkflowStacks: The tool is included in the marketplace because it's written in Swift and is designed to specifically improve AI performance on macOS.
What it does

ml-macos-performance is a Swift tool that helps optimize AI model performance on macOS devices by providing a set of utilities to improve inference speed and efficiency.

Install / run
git clone https://github.com/woolfel/ml-macos-performance.git && cd ml-macos-performance
When to use it
  • โ€ขWhen you're developing an AI-powered app on macOS and need to optimize model performance for better user experience
  • โ€ขWhen you want to compare the performance of different AI models on your macOS device
  • โ€ขWhen you need to identify performance bottlenecks in your AI-powered workflow on macOS
Quick start
  1. 1Run the command `swift build` to build the ml-macos-performance project
  2. 2Use the command `swift run MLCocoaBench` to run the Cocoa benchmarking tool
  3. 3Modify the `Sources/MLCocoaBench/main.swift` file to customize the benchmarking configuration
  4. 4Run the command `swift run MLCoreMLBench` to run the Core ML benchmarking tool
  5. 5Check the `README.md` file for more information on using the different benchmarking tools
Ready-to-paste prompt
swift run MLCocoaBench --model ResNet50 --input-size 224 --num-iterations 100
Heads up: Make sure you have the latest version of Xcode and the Swift compiler installed, as ml-macos-performance relies on Swift and Xcode to build and run the benchmarking tools
Saves to your device
What's inside โ€” free to inspect
No purchase needed

Read the entire source before you build โ€” unlike paid marketplaces that hide it behind a buy button.

3
top-level files
4
folders
57.5M
repo size
Apache-2.0
license
Key files
README.md
File tree
Data/
MLMacosPerf/
MLMacosPerf.xcodeproj/
Models/
LICENSE
README.md
results.md
Quick Actions
Details
Creator
woolfel
Language
Swift
Category
ai-agent
Published
11/8/2021

Are you the creator of this tool? Claim your listing โ†’ and earn 85% of every sale.

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