ModelPrésentéExterne

Mel Band Roformer Vocals Onnx

A host-STFT ONNX export of a Mel-Band RoFormer vocal-separation model, used by Silverdaw as its optional higher-quality vocals model. Silverdaw produces the isolated vocal stem with this model; the instrumental side...

Sourcehuggingface.co/silverdaw/mel-band-roformer-vocals-onnx/tree/6baa633eadde3c111041a81a28ed6245f19858ae

TypeOtherVersionSyhft core folded fp16 webgpuBClasse

Source du modèle

Type: Other
Taille du fichier: 5,06 MB
Version: vSyhft core folded fp16 webgpu
Mis à jour: 11 oct. 2026
Source: Hugging Face

Description de la source

Silverdaw Vocal Quality Pack — Mel-Band RoFormer (ONNX)

A host-STFT ONNX export of a Mel-Band RoFormer vocal-separation model, used by Silverdaw as its optional higher-quality vocals model. Silverdaw produces the isolated vocal stem with this model; the instrumental side is reconstructed as the residual (mix − vocals).

The torch.stft / torch.istft are stripped out of the graph: the ONNX core consumes a precomputed STFT and returns per-bin complex masks, and the host application runs the STFT, applies the masks, and runs the iSTFT.

This repository is a re-host of musetric/vocal-separation-roformer-onnx so Silverdaw can serve the file from a stable, self-owned location. The weights and the export are unchanged (byte-identical; same SHA-256).

Files

File	Size	Notes
`syhft_core_folded_fp16_webgpu.onnx`	~5 MB	The neural-core graph.
`syhft_core_folded_fp16_webgpu.onnx.data`	~707 MB	External fp16 weights. Must sit beside the `.onnx` — the graph references it by exact filename; ONNX Runtime loads it automatically.

I/O contract (host pipeline)

STFT — n_fft = 2048, hop = 441, 44.1 kHz, periodic Hann window, reflect ("centre") padding by n_fft/2. One chunk = hop × (frames − 1) samples (≈ 11 s, frames = 1101).
Tensor — [1, 2050, 1101, 2] = (batch, (n_fft/2 + 1) × channels, frames, complex), with packed bin index 2 × freq + channel.
Mask — the model returns a complex mask of the same shape; the host applies it by complex multiplication onto the STFT, then runs an envelope-normalised iSTFT and a chunk-level overlap-add. Track-level recombination is a Hamming overlap-add (8 s step over the ~11 s window) with peak normalisation.

Provenance & license

License: MIT.

Weights — © Kimberley Jensen / SYH99999 (SYH99999/MelBandRoformerBigSYHFTV1Fast; "Kim Vocal 2" / SYHFT lineage).
ONNX export — © musetric (musetric/vocal-separation-roformer-onnx).
Architecture — Mel-Band RoFormer (Wang, Lu, Won; arXiv:2310.01809) / lucidrains/BS-RoFormer (MIT).

Note on training data: the upstream training-data provenance is undocumented; the weights are distributed by their author under MIT. This re-host treats them as MIT-licensed accordingly, the same posture taken by other openly-distributed separation models.

Intended use

Designed for offline (non-real-time) vocal separation inside a desktop DAW. It is not a real-time audio-callback model — run it on a worker/background thread.

Sources

1 source

Hugging FacePrincipalVersion 6baa633eadde3c111041a81a28ed6245f19858ae

huggingface.co/silverdaw/mel-band-roformer-vocals-onnx/tree/6baa633eadde3c111041a81a28ed6245f19858ae

Vérifié 11 oct.

Artefacts du modèle

1 artefact

syhft_core_folded_fp16_webgpu.onnx

onnx · 5,06 MB · SHA-256 dde2bfe8f85d…e918 · Hugging Face

Download file

Extraits de sources

2 extraits

Readme2 aoûthuggingface.co/silverdaw/mel-band-roformer-vocals-onnx

--- license: mit library_name: onnxruntime pipeline_tag: audio-to-audio tags: - onnx - onnxruntime - audio - music - source-separation - stem-separation - mel-band-roformer - roformer - vocals - instrumental --- # Silverdaw Vocal Quality Pack — Mel-Band RoFormer (ONNX) A host-STFT ONNX export of a **Mel-Band RoFormer** vocal-separation model, used by [Silverdaw](https://github.com/irarainey/silverdaw) as its optional higher-quality **vocals** model. Silverdaw produces the isolated vocal stem with this model; the instrumental side is reconstructed as the residual (`mix − vocals`). The `torch.stft` / `torch.istft` are stripped out of the graph: the ONNX core consumes a precomputed STFT and returns per-bin complex masks, and the host application runs the STFT, applies the masks, and runs the iSTFT. This repository is a **re-host** of [`musetric/vocal-separation-roformer-onnx`](https://huggingface.co/musetric/vocal-separation-roformer-onnx) so Silverdaw can serve the file from a stable, self-owned location. The weights and the export are unchanged (byte-identical; same SHA-256). ## Files | File | Size | Notes | | --- | --- | --- | | `syhft_core_folded_fp16_webgpu.onnx` | ~5 MB | The neural-core graph. | | `syhft_core_folded_fp16_webgpu.onnx.data` | ~707 MB | External fp16 weights. **Must sit beside the `.onnx`** — the graph references it by exact filename; ONNX Runtime loads it automatically. | ## I/O contract (host pipeline) - **STFT** — `n_fft = 2048`, `hop = 441`, 44.1 kHz, periodic Hann window, reflect ("centre") padding by `n_fft/2`. One chunk = `hop × (frames − 1)` samples (≈ 11 s, `frames = 1101`). - **Tensor** — `[1, 2050, 1101, 2]` = (batch, `(n_fft/2 + 1) × channels`, frames, complex), with packed bin index `2 × freq + channel`. - **Mask** — the model returns a complex mask of the same shape; the host applies it by complex multiplication onto the STFT, then runs an envelope-normalised iSTFT and a chunk-level overlap-add. Track-level recombination is a Hamming overlap-add (8 s step over the ~11 s window) with peak normalisation. ## Provenance & license **License: MIT.** - **Weights** — © Kimberley Jensen / SYH99999 (`SYH99999/MelBandRoformerBigSYHFTV1Fast`; "Kim Vocal 2" / SYHFT lineage). - **ONNX export** — © musetric ([`musetric/vocal-separation-roformer-onnx`](https://huggingface.co...

Note2 aoûthuggingface.co/silverdaw/mel-band-roformer-vocals-onnx

Source context: 0 downloads · 1 likes · Pipeline audio-to-audio · Library onnxruntime · Repo silverdaw/mel-band-roformer-vocals-onnx