---
license: mit
tags:
  - coreml
  - audio
  - source-separation
---

# Spleeter 2stems for Core ML (vocal mask, 1536 bins, FP16)

A Core ML conversion of [Spleeter](https://github.com/deezer/spleeter)'s pretrained 2stems model (v1.4.0) by Deezer, used to separate voice from music in Clarity Sound Studio, a free, open-source macOS app.

| | |
| --- | --- |
| File | `Spleeter2StemsVocalMask-F1536-fp16.mlmodelc` (compiled ML Program, FP16, macOS 14+) |
| Upstream | `2stems.tar.gz`, SHA-256 `f3a90b39dd2874269e8b05a48a86745df897b848c61f3958efc80a39152bd692` |
| Conversion | The two U-Nets re-implemented in PyTorch (matching TensorFlow at a median 72 dB SNR), then `spleeter_torch.py convert --f-bins 1536` with coremltools and `coremlcompiler` |
| Input | `magnitude`, float32 (1, 2, 512, 1536): a stereo magnitude spectrogram |
| Output | `vocal_mask`, float32, same shape: the vocal ratio mask, `sv² / (sv² + sa² + 1e-6)` |

The weights are unchanged apart from the conversion to FP16.

## Licence

MIT licence; see `LICENSE`. Copyright (c) 2019-present Deezer SA.

> R. Hennequin, A. Khlif, F. Voituret and M. Moussallam, "Spleeter: a fast and efficient music source separation tool with pre-trained models", Journal of Open Source Software 5(50), 2154, 2020.