Laya (OS Jev) on Mac M4 CoreML Offline (45 decisions per second)
Recorded: Sept. 20, 2026, 5 p.m.
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Laya on Mac m4 CoreML Offline · GitHub Skip to content
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Save fordnox/e592d0f68b543fd044be8e6d040863a0 to your computer and use it in GitHub Desktop. Download ZIP Laya on Mac m4 CoreML Offline laya.sh mkdir test-laya cd test-laya uv init uv add 'laya-coreml[demo]' hf download aac6fef/laya-multilingual-coreml-ane --local-dir models/snake uv run laya-coreml-snake --model models/snake fordnox
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The provided material outlines a process for executing Laya with CoreML functionality offline on a Mac with an M4 chip, presented via a series of command-line instructions from a GitHub Gist. The workflow is designed to set up and run Laya models, specifically demonstrating an offline capability. The initial steps involve setting up a local testing environment by creating a directory named test-laya and navigating into it. Subsequently, the process utilizes the uv package manager to initialize a project and install necessary dependencies, specifically adding the 'laya-coreml[demo]' package. The core of the procedure involves downloading a specific Laya multilingual CoreML model from the Hugging Face repository, which is sourced with the identifier aac6fef/laya-multilingual-coreml-ane, and saving it to a local directory structure. This downloaded model is placed within a models/snake subdirectory. Finally, the execution step runs the Laya application utilizing the installed CoreML components and referencing the previously downloaded model, specifically invoking laya-coreml-snake with the model path defined. This sequence demonstrates the practical steps required to initialize a software environment, acquire necessary machine learning assets offline, and execute a complex model inference process using CoreML on Apple silicon hardware. The reference also points to related testing code, suggesting an emphasis on reproducible and verifiable implementation within the framework. |