Create README.md

README.md

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+---
+base_model: facebook/mms-tts-mlg
+library_name: transformers.js
+pipeline_tag: text-to-speech
+tags:
+- text-to-audio
+---
+
+https://huggingface.co/facebook/mms-tts-mlg with ONNX weights to be compatible with Transformers.js.
+
+## Usage (Transformers.js)
+
+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:
+```bash
+npm i @xenova/transformers
+```
+
+**Example:** Generate Malagasy speech with `elloza/mms-tts-mlg`.
+```js
+import { pipeline } from '@xenova/transformers';
+
+// Create a text-to-speech pipeline
+const synthesizer = await pipeline('text-to-speech', 'elloza/mms-tts-mlg', {
+    quantized: false, // Remove this line to use the quantized version (default)
+});
+
+// Generate speech
+const output = await synthesizer('manao ahoana');
+console.log(output);
+// {
+//   audio: Float32Array(10752) [ ... ],
+//   sampling_rate: 16000
+// }
+```
+
+Optionally, save the audio to a wav file (Node.js):
+```js
+import wavefile from 'wavefile';
+import fs from 'fs';
+
+const wav = new wavefile.WaveFile();
+wav.fromScratch(1, output.sampling_rate, '32f', output.audio);
+fs.writeFileSync('out.wav', wav.toBuffer());
+```
+
+<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/-6E56kNCnXUQrLAkR7fuZ.wav"></audio>
+
+---
+
+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`).