AEmotionStudio / roformer-models

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audio-to-audio

Introduction of roformer-models

Model Details of roformer-models

RoFormer Stem Separation Models (Safetensors)

BS-RoFormer & MelBand RoFormer — State-of-the-art music source separation

Pretrained weights converted to safetensors format for use with Mæstræa AI Workstation .

Models
BS-RoFormer (Band-Split RoPE Transformer)
Variant SDR Task Path
Vocals (viperx) 12.97 Vocal/instrumental separation bs_roformer/vocals_viperx/
Multi-stem 9.65 4-stem (bass/drums/vocals/other) bs_roformer/multistem/
MelBand RoFormer (Mel-Band RoPE Transformer)
Variant SDR Task Path
Vocals (KimberleyJensen) 10.98 Best vocal isolation mel_band_roformer/vocals_kj/
Vocals (viperx) 11.43 Vocal/instrumental separation mel_band_roformer/vocals_viperx/
Dereverb (anvuew) 19.17 Remove reverb from audio mel_band_roformer/dereverb/
Denoise (aufr33) 27.99 Remove noise from audio mel_band_roformer/denoise/
Architecture

Both models use the Band-Split RoPE Transformer architecture from lucidrains/BS-RoFormer :

  • BS-RoFormer : Splits spectrogram into uniform-width subbands
  • MelBand RoFormer : Splits using mel-scale (perceptually-weighted) overlapping bands

Both significantly outperform HTDemucs on vocal separation tasks.

Usage

Each model directory contains:

  • model.safetensors — Model weights
  • config.yaml — Architecture configuration (required for model instantiation)

Requires bs-roformer Python package: pip install bs-roformer

Credits
License

MIT — same as all upstream model releases.

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Updated:February 25 2026