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Check out the documentation for more information.
A MIDI transcription model focuses on vocal, fine-tuned on the MIR-ST500 Chinese vocal.
Files
model.pt- inference weights.config.json- model/audio/task configuration.r47b_infer.py- local vocal stem to MIDI CLI.runtime_deps/,yourmt3_train_src/- minimal runtime source.
Usage
pip install -r requirements.txt
python r47b_infer.py vocals.wav --output-midi vocals.mid --device cuda
Input should be a separated vocal stem.
Metrics
Metrics are reported on MIR-ST500 vocal transcription splits; this model repo does not include dataset audio or labels.
| Route | Split | COnP-F1 | COn-F1 | COnPOff-F1 |
|---|---|---|---|---|
r47b direct model.pt |
official82 | 0.6882375797 |
0.6882375797 |
0.5143113621 |
| r47b + E12 single-source | official82 | 0.7181716362 |
0.7624981992 |
0.5220578867 |
| r47b + E12 single-source | train337/calib | 0.7468827545 |
0.7744380415 |
0.5575166125 |
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