| HDEMUCS_HIGH_MUSDB_PLUS**     |  9.37 | 11.38 |  10.53 |  7.24 |   8.32 |
* Trained on the training data of MUSDB-HQ dataset.** Trained on both training and test sets of MUSDB-HQ and 150 extra songs from an internal database that were specifically produced for Meta.
from torchaudio.pipelines import HDEMUCS_HIGH_MUSDB_PLUS

bundle = HDEMUCS_HIGH_MUSDB_PLUS
model = bundle.get_model()
sources_list = model.sources

mixture, samplerate = torchaudio.load("song.wav")
sources = model(mixture)
audios = dict(zip(sources_list, sources)

Special thanks to Alexandre Defossez for the guidance.
(Beta) Datasets and Metadata Mode for SUPERB Benchmark