laya-mlx
by mizorewww
Runs Laya typed-decision models locally on Apple Silicon using MLX
Native MLX runtime for Laya typed decision models — 7–14 ms short decisions on M3 Max. No text generation, PyTorch, or cloud API.
On X
laya-mlx plays Snake at 60 decisions per second on an M3 Max
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！
Project: laya-mlx→
Laya-mlx processes 20 Chinese support tickets in 25 ms
Jev 发布才 8 天，开源替身已经一堆了，今天诺基亚也来蹭热闹了😅 我在 MacBook 上，让官方 Jev 和 3 个开源方案同跑 20 张中文工单🫱 Laya 25ms，比 Jev 快 50 倍 djev 509ms 官方 Jev 1.3 秒 AnyJev 将近 4 秒 仓库都在这： Laya（Mac 版） djev（Mac 版） AnyJev 但快的，不一定对 👇
Project: laya-mlx→
laya-mlx plays Snake at 60 decisions per second on an M3 Max
Laya-MLX is an open source classification system similar to Jev but 50x faster, running locally on device with a maximum of 1GB memory and making decisions at 60 per second, fast enough to play Snake on an M3 Max at full speed. Repo here:
Project: laya-mlx→
laya-mlx plays Tetris built with Claude
Laya-mlx is INSANE. Built Tetris (Claude) and let Laya play it. You can speed up/down the game (kudos
Project: laya-mlx→
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