Implements high-performance local machine learning inference in the browser using ONNX Runtime Web. Use this skill when the user needs privacy-first, low-latency, or offline AI capabilities (e.g., image classification, object detection, or NLP) without server-side processing.
Quickly install browser-onnx AI skill to your development environment via command line
Source: thongnt0208/browser-onnx-skills.
This skill provides a comprehensive workflow for executing ONNX models locally in the browser using ONNX Runtime Web (ORT-Web). Local inference offers significant advantages in data privacy, reduced server costs, and unlimited scalability as each user brings their own compute power.
Note: For experimental features like WebGPU or WebNN, use the nightly version onnxruntime-web@dev.
Set global ort.env flags before creating a session to optimize the runtime environment.
Implements high-performance local machine learning inference in the browser using ONNX Runtime Web. Use this skill when the user needs privacy-first, low-latency, or offline AI capabilities (e.g., image classification, object detection, or NLP) without server-side processing. Source: thongnt0208/browser-onnx-skills.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/thongnt0208/browser-onnx-skills --skill browser-onnxImplements high-performance local machine learning inference in the browser using ONNX Runtime Web. Use this skill when the user needs privacy-first, low-latency, or offline AI capabilities (e.g., image classification, object detection, or NLP) without server-side processing. Source: thongnt0208/browser-onnx-skills.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/thongnt0208/browser-onnx-skills --skill browser-onnx Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/thongnt0208/browser-onnx-skills