| --- |
| license: apache-2.0 |
| base_model: RSNuts/Universal_Source_Separation |
| tags: |
| - mlx |
| - audio |
| - audio-to-audio |
| - source-separation |
| --- |
| |
| # USS ResUNet30 (MLX) |
|
|
| Universal source separation — extracts a chosen sound class from a mixture. |
| Converted to MLX from the [ByteDance USS](https://github.com/bytedance/uss) code |
| and the published |
| [RSNuts/Universal_Source_Separation](https://huggingface.co/RSNuts/Universal_Source_Separation) |
| checkpoint. |
|
|
| ## Files |
|
|
| | file | size | |
| | --- | ---: | |
| | `resunet30_fp32.safetensors` | 102 MiB | |
| | `resunet30_fp16.safetensors` | 51 MiB | |
|
|
| ## Precision |
|
|
| | precision | size | speed | peak memory | quality vs fp32 | |
| | --- | ---: | ---: | ---: | ---: | |
| | fp32 | 102 MiB | **27.2x** | **1203 MiB** | reference | |
| | fp16 | **51 MiB** | 25.8x | 1259 MiB | 57.3 dB | |
|
|
| Bold marks the best value in each column. Quality is fp16 against this model's own |
| fp32 output — the cost of the precision change, not a score for the model. |
|
|
| fp16 halves the download. On the machine below it was also slightly slower and |
| used slightly more memory than fp32, since the forward pass dominates the |
| footprint rather than the weights. |
|
|
| Measured on an Apple M1 Pro (16 GB), 30 s of audio, three timed runs per |
| configuration; speed is realtime factor. These are single-machine figures — expect |
| different absolute numbers on other hardware, and treat the ordering as indicative |
| rather than guaranteed. |
|
|
| ## Conditioning |
|
|
| USS is conditioned on a 527-dimensional vector over the |
| [AudioSet](https://research.google.com/audioset/) classes, which selects what the |
| separator extracts. It is an input rather than a model weight and is not shipped |
| here: each vector is a normalised multi-hot indicator over a class group — zero |
| everywhere, `1/n` at each of the `n` chosen indices — so a class list fully |
| determines it. |
|
|
| Class indices follow AudioSet's `class_labels_indices.csv`, published by Google |
| with the dataset under CC BY 4.0. |
|
|
| ## Used by |
|
|
| [AudioToolSwift](https://github.com/starkdmi/AudioToolSwift) |
|
|
