Convert PyTorch models into ExecuTorch .pte format for edge deployment.
npx skills add https://github.com/Msabih/executorch --skill export-msabih
Please help me install this Agent Skill. Skill: export Source: https://github.com/Msabih/executorch/tree/main/.claude/skills/export Command: npx skills add https://github.com/Msabih/executorch --skill export-msabih
Converts PyTorch models into ExecuTorch's .pte format for on-device deployment, enabling compact, portable model packages.
Run the export workflow to convert a PyTorch model into a portable .pte file ready for edge deployment.
High-intent search queries and answers about installing and using this skill.
To convert a PyTorch model for on-device deployment, you can export it into ExecuTorch's .pte format. This process generates a compact, portable model package suitable for mobile and embedded devices.
A .pte file is a portable edge artifact created by ExecuTorch. You need this format when you want to deploy a trained vision or language model to a smartphone or embedded device with a minimal runtime footprint.
Yes, you can use this export workflow to deploy both vision and language models on mobile devices. It applies a reproducible lower-to-edge workflow to transform PyTorch models into portable .pte files.
The best way to package a trained model for embedded inference is running an edge transformation workflow. This lowers your PyTorch model to a compact .pte artifact, ensuring a minimal runtime footprint on the edge device.
Yes, example scripts are available for the export process. The Skill exposes guidance via SKILL.md and accompanying guides, pointing directly to scripts that demonstrate converting PyTorch models into .pte files.
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