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README.md
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license: cc-by-nc-4.0
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---
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> [!IMPORTANT]
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> NOTE: MusicGen support is experimental and requires you to install Transformers.js [v3](https://github.com/xenova/transformers.js/tree/v3) from source.
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If you haven't already, you can install the [Transformers.js](https://huggingface.co/docs/transformers.js) JavaScript library from [GitHub](https://github.com/xenova/transformers.js/tree/v3) using:
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```bash
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npm install xenova/transformers.js#v3
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```
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**Example:** Generate music with `Xenova/musicgen-small`.
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```js
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import { AutoTokenizer, MusicgenForConditionalGeneration } from '@xenova/transformers';
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// Load tokenizer and model
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const tokenizer = await AutoTokenizer.from_pretrained('Xenova/musicgen-small');
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const model = await MusicgenForConditionalGeneration.from_pretrained('Xenova/musicgen-small', {
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dtype: {
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text_encoder: 'q8',
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decoder_model_merged: 'q8',
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encodec_decode: 'fp32',
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},
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});
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// Prepare text input
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const prompt = 'a light and cheerly EDM track, with syncopated drums, aery pads, and strong emotions bpm: 130';
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const inputs = tokenizer(prompt);
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// Generate audio
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const audio_values = await model.generate({
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...inputs,
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max_new_tokens: 500,
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do_sample: true,
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guidance_scale: 3,
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});
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// (Optional) Write the output to a WAV file
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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, model.config.audio_encoder.sampling_rate, '32f', audio_values.data);
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fs.writeFileSync('musicgen.wav', wav.toBuffer());
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```
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<audio controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/cJ9HFIDstOqJN0eGyJwlS.wav"></audio>
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We also released an online demo, which you can try yourself: https://huggingface.co/spaces/Xenova/musicgen-web
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<video controls src="https://cdn-uploads.huggingface.co/production/uploads/61b253b7ac5ecaae3d1efe0c/zc43B_VuUVJm4kOJPOHNh.mp4"></video>
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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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license: cc-by-nc-4.0
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---
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# Avasaz ONNX (In Browser model)
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Based on [Xenova](https://huggingface.co/xeonva/musicgen-small)'s ONNX quantization.
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