AudioSR basic, trimmed

The released AudioSR basic checkpoint, cut down to what super-resolution runs and saved as safetensors. It is used by IntelligenceKit's MLXAudioSR (Swift, MLX) and by afm upscale.

basic.safetensors, 2.69 GB, float32, with PyTorch names and layouts. It holds:

  • model.: the diffusion UNet
  • first_stage_model.: the VAE and its 48 kHz HiFi-GAN vocoder
  • the scale factor and the noise schedule's buffers

These are left out:

  • CLAP, which super-resolution doesn't use;
  • the EMA copy of the UNet, since inference uses the live weights;
  • the condition encoder's VAE, which is identical to first_stage_model.

The MLX port casts to float16 at load time.

convert.py, the script that made the file:

python convert.py basic basic.safetensors

Parity

The MLX port matches PyTorch stage by stage, from 76 to 137 dB SNR. It was tested on a clip low-passed at 6 kHz and scored by LSD against the original (lower is better):

LSD
input 3.88
PyTorch 1.16
MLX 1.14
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