Reduced on GPU (thanks and new multi-core evaluation on CPU ( -j flag). : Releasing v3.0.3: bug fixes (thanks memory drastically.: Releasing v3.0.4: split into two stems (i.e.: Releasing v3.0.5: Set split segment length to reduce memory.: added reproducibility and ablation grids, along with an updated version of the paper.: Added the new Hybrid Transformer Demucs v4 models.Īdding support for the torchaudio implementation of HDemucs.Also releasingĪ 6 sources models (adding guitar and piano, although the latter doesn't work so well at the moment). : added support for the SDX 2023 Challenge,.Important news if you are already using Demucs Quick testing seems to show okay quality for guitar, but a lot of bleeding and artifacts for the piano source. We are also releasing an experimental 6 sources model, that adds a guitar and piano source. Requires custom CUDA code that is not ready for release yet. The Sparse Hybrid Transformer model decribed in our paper is not provided as its The single, non fine-tuned model is provided as -n htdemucs, and the retrained baselineĪs -n hdemucs_mmi. This model separates drums, bass and vocals and other stems for any song.Īs Hybrid Transformer Demucs is brand new, it is not activated by default, you can activate it in the usualĬommands described hereafter with -n htdemucs_ft. It has been trained on the MUSDB HQ dataset + an extra training dataset of 800 songs. Samples are available on our sample page. Kernels to extend its receptive field and per source fine-tuning, we achieve state-of-the-art 9.20 dB of SDR. The model achieves a SDR of 9.00 dB on the MUSDB HQ test set. This Transformer uses self-attention within each domain, Replaced by a cross-domain Transformer Encoder. It is based on Hybrid Demucs (also provided in this repo) with the innermost layers are The v4 version features Hybrid Transformer Demucs, a hybrid spectrogram/waveform separation model using Transformers. You can also go Demucs v2.ĭemucs is a state-of-the-art music source separation model, currently capable of separatingĭrums, bass, and vocals from the rest of the accompaniment.ĭemucs is based on a U-Net convolutional architecture inspired by Wave-U-Net. If you are experiencing issues and want the old Demucs back, please fill an issue, and then you can get back to the v3 with This is the 4th release of Demucs (v4), featuring Hybrid Transformer based source separation.įor the classic Hybrid Demucs (v3): Go this commit.
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