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            https://huggingface.co/openai/whisper-large-v2 with ONNX weights to be compatible with Transformers.js.
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            If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/transformers) using:
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            ```bash
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            npm i @huggingface/transformers
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            ```
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            Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).
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            https://huggingface.co/openai/whisper-large-v2 with ONNX weights to be compatible with Transformers.js.
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            ## Usage (Transformers.js)
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            If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [NPM](https://www.npmjs.com/package/@huggingface/transformers) using:
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            ```bash
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            npm i @huggingface/transformers
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            ```
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            **Example:** Transcribe audio from a URL.
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            ```js
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            import { pipeline } from '@huggingface/transformers';
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            const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-large-v2');
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            const url = 'https://huggingface.co/datasets/Xenova/transformers.js-docs/resolve/main/jfk.wav';
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            const output = await transcriber(url);
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            ```
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            Note: Having a separate repo for ONNX weights is intended to be a temporary solution until WebML gains more traction. If you would like to make your models web-ready, we recommend converting to ONNX using [🤗 Optimum](https://huggingface.co/docs/optimum/index) and structuring your repo like this one (with ONNX weights located in a subfolder named `onnx`).
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