Laya-MLX is an independent MLX implementation of Laya’s typed decision models for Apple Silicon Macs. It performs structured choice, score, and probability decisions without token-by-token text generation. Inference runs fully locally after model weights are downloaded and does not require PyTorch, Transformers, or a cloud API. The runtime supports English, multilingual, and typed-decision Laya checkpoints while preserving their original calibration and output formats. Its implementation moves the encoder, decision transformer, scoring head, and action head into MLX. The project reports short-decision latency in the single-digit to low-teens millisecond range on an M3 Max, depending on the checkpoint. It also includes routing utilities, demos, validation tests, benchmarks, and a Python API.

Features

  • Native Apple Silicon MLX inference
  • Choice, score, and probability decisions
  • Fully local execution
  • English and multilingual checkpoints
  • Python API and model routing
  • Benchmarks, validation tests, and demos

Project Samples

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Categories

AI Models

License

Apache License V2.0

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Additional Project Details

Programming Language

Python

Related Categories

Python AI Models

Registered

13 hours ago