Magenta RT 2 — Quantized Acoustic Distillation (QAD) ONNX
This repository hosts the Quantized Acoustic Distillation (QAD) ONNX models for real-time neural music generation in the browser via WebGPU and WASM SIMD.
Architecture & Model Components
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authentic_student_generator_int8.onnx(64.0 MB):- Unrolled 12-codebook Depthformer student model (6 temporal layers, 2 depth layers, 35.7M active parameters).
- Generates 12 hierarchical Residual Vector Quantizer (RVQ) acoustic codes causally per 40 ms frame in ~39 ms on CPU (~12 ms on WebGPU).
- Conditioned on 768-dim
MusicCoCastyle embeddings and 128-element MIDI chord/note vectors.
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authentic_spectrostream_decoder_int8.onnx(41.9 MB):- Full 35.6M-parameter SpectroStream neural vocoder.
- Converts 12 RVQ codes into 48 kHz stereo PCM audio via convolutional frame expansion, harmonic synthesis, and WebGPU/WASM-native MatMul IDFT overlap-add.
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style_embeddings.json(144 KB):- Precomputed 768-dimensional latent style vectors across curated genres: Lo-Fi, Chill-Hop, Smooth Jazz, Synthwave, Deep Ambient, Classical, Rock, Funk, and Cinematic.
Direct CDN & Download Links
authentic_student_generator_int8.onnx:https://huggingface.co/JustACluelessKidAtSchool/magenta-rt-2-qad-onnx/resolve/main/authentic_student_generator_int8.onnxauthentic_spectrostream_decoder_int8.onnx:https://huggingface.co/JustACluelessKidAtSchool/magenta-rt-2-qad-onnx/resolve/main/authentic_spectrostream_decoder_int8.onnxstyle_embeddings.json:https://huggingface.co/JustACluelessKidAtSchool/magenta-rt-2-qad-onnx/resolve/main/style_embeddings.json
In-Browser Deployment
Designed for 100% client-side zero-backend browser execution in:
music_studio.html: Interactive live jam studio with prompt latent surface and keyboard steering.focus_radio.html: Continuous endless AI radio stream with ambient soundscape mixer.- Models are cached into browser
IndexedDB(CascadeOfflineMusicDB) on first download for permanent offline execution.