resemble-enhance-mlx

MLX-compatible safetensors for resemble-enhance, converted for use with resemble-enhance-swift on Apple Silicon.

These are the original Resemble AI weights, transformed for the MLX layout. No retraining or fine-tuning has been done.

Files

File	Size	Purpose
denoiser.safetensors	41 MB	2D UNet spectral-mask denoiser
lcfm_ae.safetensors	390 MB	IRMAE encoder/decoder (mel <-> 64-dim latent)
lcfm_cfm.safetensors	264 MB	Conditional flow matching, 30-layer WaveNet velocity field
vocoder.safetensors	662 MB	UnivNet vocoder (LVCNet generator)
normalizer.safetensors	160 B	Mel running mean/variance

Total: ~1.4 GB at float32.

Usage

With resemble-enhance-swift:

huggingface-cli download sammcj/resemble-enhance-mlx

The CLI and example SwiftUI app auto-discover weights from the HuggingFace hub cache (~/.cache/huggingface/hub/models--sammcj--resemble-enhance-mlx/snapshots/<commit>/). You can also pass the directory explicitly:

resemble-enhance enhance \
  --model-dir ~/.cache/huggingface/hub/models--sammcj--resemble-enhance-mlx/snapshots/<commit>/ \
  input.wav output.wav

Or from Swift:

import ResembleEnhance

let engine = try ResembleEnhance(modelDirectory: weightsURL)
let enhanced = engine.enhance(samples: samples, sampleRate: 24_000)

Conversion

Produced by Scripts/convert_weights.py in resemble-enhance-swift. The script:

1. Loads mp_rank_00_model_states.pt from the upstream PyTorch checkpoint (DeepSpeed format, wrapped in ["module"])
2. Fuses weight_norm parametrisations into plain weight tensors (handles both old weight_g/weight_v and new parametrizations.weight.original* formats)
3. Transposes conv kernels from PyTorch NCHW to MLX NHWC layout (Conv1d O,I,K -> O,K,I; Conv2d O,I,H,W -> O,H,W,I; ConvTranspose1d I,O,K -> O,K,I)
4. Transposes FIR filter buffers used by the alias-free resampler (same layout, since they're applied as conv kernels)
5. Splits the monolithic checkpoint into one safetensors file per component
6. Strips unused buffers (dummy, mel_fn, mrstft, training-only estimator)

To reproduce:

huggingface-cli download ResembleAI/resemble-enhance
python Scripts/convert_weights.py

The output then matches what's in this repo.

Source

Derived from ResembleAI/resemble-enhance. The original PyTorch checkpoint is mp_rank_00_model_states.pt from the enhancer_stage2 training run.

Licence and credit

Released under CC-BY-NC-4.0, inheriting the upstream licence. Non-commercial use only.

The model architecture, training data, training code, and original weights are the work of Resemble AI. This repo only contains the format conversion required to run the model on Apple Silicon via MLX. All credit for the model itself belongs to the original authors:

• resemble-enhance
• Resemble AI