womogenes/musicgen-interp

Interpreting generative music models

0

stars

59

commits

Jupyter Notebook

primary language

Dec 10, 2025

updated

README

MusicGen interpretability

https://musicgen.com

Setup

  1. Install uv (https://docs.astral.sh/uv)
  2. uv sync

Reference

https://github.com/facebookresearch/audiocraft

MIDI

midi/make_dataset.py generates audio files with basic prompts and puts them in data/audio/*.wav, data/midi/*.midi, and data/activations/*.pt.

MusicGen Architecture

  • EnCodec encoder: converts raw audio samples to "cookbook codec" (4 streams, each at 50 Hz with a dictionary of 2048 tokens).
  • Embedding layer: converts tokens into vectors (standard)
  • Transformer (decoder): turns tokens into next tokens (one for each of the 4 streams)

Contributors

womogenes

31 commits

harini-tt

15 commits

michelle-weii

13 commits

womogenes/musicgen-interp

Interpreting generative music models

0

stars

59

commits

Jupyter Notebook

primary language

Dec 10, 2025

updated

README

MusicGen interpretability

https://musicgen.com

Setup

  1. Install uv (https://docs.astral.sh/uv)
  2. uv sync

Reference

https://github.com/facebookresearch/audiocraft

MIDI

midi/make_dataset.py generates audio files with basic prompts and puts them in data/audio/*.wav, data/midi/*.midi, and data/activations/*.pt.

MusicGen Architecture

  • EnCodec encoder: converts raw audio samples to "cookbook codec" (4 streams, each at 50 Hz with a dictionary of 2048 tokens).
  • Embedding layer: converts tokens into vectors (standard)
  • Transformer (decoder): turns tokens into next tokens (one for each of the 4 streams)

Contributors

womogenes

31 commits

harini-tt

15 commits

michelle-weii

13 commits

Languages

Jupyter Notebook

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