Experimenting with the proposed Cross-Origin Storage API in Transformers.js

Updated September 26, 2026 · 2:44 PM · source date June 23, 2026

Summary

Experimenting with the proposed Cross-Origin Storage API in Transformers.js Experimenting with the proposed Cross-Origin Storage API in Transformers.js Published June 23, 2026 Update on GitHub Upvote 8 Thomas Steiner tomayac google (This is a guest post by Developer Relations Engineer Thomas Steiner from the Chrome team at Google.) Transformers.js provides Web developers with a simple way to use the power of transformers in their Web apps through task-specific pipelines. To run inference in the browser, developers create an instance of pipeline() and specify a task they want to use the pipeline for.

Why it matters

This OpenSourceRelease is relevant to the technology intelligence record because it involves GitHub, Google, Hugging Face, Llama. The source article should remain the factual reference for follow-up coverage.

Key facts

Experimenting with the proposed Cross-Origin Storage API in Transformers.js Published June 23, 2026 Update on GitHub Upvote 8 Thomas Steiner tomayac google (This is a guest post by Developer Relations Engineer Thomas Steiner from the Chrome team at Google.) Transformers.js provides Web developers with a simple way to use the power of transformers in their Web apps through task-specific pipelines.
To run inference in the browser, developers create an instance of pipeline() and specify a task they want to use the pipeline for.
As a concrete example, the following snippet shows how to set up an automatic speech recognition (ASR) pipeline.
import { pipeline } from 'https://cdn.jsdelivr.net/npm/@huggingface/[email protected]' ; const asr = await pipeline ( 'automatic-speech-recognition' , 'Xenova/whisper-tiny.en' , { device : 'webgpu' }, ); const result = await asr ( 'jfk.wav' ); console .
log (result); The cache challenge You will notice in the source code that I specified Xenova/whisper-tiny.en as the model, which is a very decent choice for common English automatic speech recognition tasks.
In fact, it's even the default model according to the Transformers.js default model resolution , as per the linked excerpt .

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