Meet Husky: a Model-Specific Inference (MSI) engine up to 4.5× faster than Apple's MLX Woof, Underdog's Pareto frontier model, now runs up to 730 tokens/sec on a MacBook Finally local models are as fast & capable. Try it now in underdog.ai - your personal private AI↗

介绍比Jev快50倍，在你设备上跑的laya-mlx! 只在你的设备上占用最高1G内存 Laya是一个开源的类似于Jev的,基于文本输出概率的分类系统 我将其移植到MLX,并且做了一些性能优化! 视频中就是这个模型在我的本地M3Max上玩贪吃蛇 这个模型能够以每秒决策60次的速度玩贪吃蛇！ github.com/mizorewww/laya…↗

Have you built a language model? You should. It's so much fun to chat with something you made. Anyone can do it, too. I made an app that teaches the fundamentals and gives you everything you need to build your own: languagemodelbuilder.com↗