README.md

metadata

license: mit
library_name: onnxruntime
pipeline_tag: audio-to-audio
tags:
  - music-source-separation
  - htdemucs
  - demucs
  - onnx
  - onnxruntime-web
  - webgpu
  - stem-separation

HTDemucs 6S for ONNX Runtime Web (Audisect build)

Browser-ready ONNX build of HTDemucs 6S (Hybrid Transformer Demucs, 6 sources), used by Audisect, a free stem splitter that runs entirely in the browser.

File	Size	SHA-256
htdemucs_6s_web.onnx	142,808,361 bytes	76d177e4cfd7da6aad46e540c5dc929a80f5e839d306a285265f9ec49a28a1ea

Inputs and outputs

• Input mix: float32 [1, 2, 343980], stereo, 44.1 kHz, 7.8 s, values in [-1, 1].
• Output: float32 [1, 6, 2, 343980], stems in order drums, bass, other, vocals, guitar, piano.

Process longer audio in overlapping 7.8 s chunks and crossfade the results.

How this file was made

It is derived from StemSplitio/htdemucs-6s-onnx (htdemucs_6s_fp16weights.onnx) with Audisect's scripts/prepare_model.py:

1. float64 constants in the iSTFT converted to float32 (ONNX Runtime Web has no float64 ConstantOfShape),
2. graph constant-folded with ONNX Runtime's basic optimisations (24,819 to 1,436 nodes),
3. weights stored as float16 with Cast nodes.

Checked against the source model on random input: relative RMS error about 3e-5.

License and attribution

MIT, same as the upstream weights and export.

• Model: HTDemucs by Meta AI Research, facebookresearch/demucs (MIT).
• Paper: Simon Rouard, Francisco Massa, Alexandre Défossez, Hybrid Transformers for Music Source Separation, ICASSP 2023.
• ONNX export: StemSplit (MIT).