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--- |
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base_model: facebook/mms-tts-rus |
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library_name: transformers.js |
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pipeline_tag: text-to-speech |
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tags: |
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- text-to-audio |
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--- |
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https://huggingface.co/facebook/mms-tts-rus 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/@xenova/transformers) using: |
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```bash |
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npm i @xenova/transformers |
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``` |
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**Example:** Generate Russian speech with `Xenova/mms-tts-rus`. |
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```js |
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import { pipeline } from '@xenova/transformers'; |
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// Create a text-to-speech pipeline |
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const synthesizer = await pipeline('text-to-speech', 'Xenova/mms-tts-rus', { |
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quantized: false, // Remove this line to use the quantized version (default) |
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}); |
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// Generate speech |
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const output = await synthesizer('Привет'); |
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console.log(output); |
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// { |
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// audio: Float32Array(11264) [ ... ], |
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// sampling_rate: 16000 |
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// } |
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``` |
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Optionally, save the audio to a wav file (Node.js): |
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```js |
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import wavefile from 'wavefile'; |
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import fs from 'fs'; |
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const wav = new wavefile.WaveFile(); |
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wav.fromScratch(1, output.sampling_rate, '32f', output.audio); |
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fs.writeFileSync('out.wav', wav.toBuffer()); |
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``` |
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<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/-h1r1q5_MnZBixZ2Qbw3z.wav"></audio> |
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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`). |