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README.md
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@@ -16,13 +16,13 @@ npm i @huggingface/transformers
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import { pipeline } from '@huggingface/transformers';
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// Create the pipeline
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const
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dtype: 'fp32', // Options: "fp32", "fp16", "q8", "q4"
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});
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// Use the model
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const
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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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import { pipeline } from '@huggingface/transformers';
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// Create the pipeline
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const transcriber = await pipeline('automatic-speech-recognition', 'Xenova/whisper-base', {
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dtype: 'fp32', // Options: "fp32", "fp16", "q8", "q4"
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});
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// Use the model
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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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