Running Quantized ViT Models in the Browser with WebAssembly for Privacy-First Vision AI

Short summary

This tutorial demonstrates running a quantized Vision Transformer (ViT) model entirely in the browser using TensorFlow.js and WebAssembly for privacy-first skin lesion analysis. The approach eliminates server-side data storage, removes API round-trip latency, and incurs zero inference costs by leveraging the user's local hardware. Code examples cover WASM backend initialization, model loading, image preprocessing, and prediction, with production tips on model sharding and Web Worker isolation.

• •Run quantized ViT models in-browser via TensorFlow.js + WASM for zero-data-leave-device inference
• •Covers WASM init, model loading, tensor preprocessing, and prediction with code examples
• •Targets healthcare use case (skin lesion screening) with sub-second latency and no API costs

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