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magenta/mt3

MT3: Multi-Task Multitrack Music Transcription observed · 2026-08-28

github.com/magenta/mt3 · Python · Apache-2.0 (permissive) observed · 2026-08-28

Health v2 · maintenance only

73/100

  • Activity 91
  • Release rhythm 35
  • Longevity 100

Flags: no_releases

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-03. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 1764
  • days_rel: n/a
  • days_push: 55
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

1744 stars · 223 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

MT3 is a multi-instrument automatic music transcription model built on the T5X framework, converting audio recordings into multitrack MIDI. It provides pretrained checkpoints for piano and multi-instrument transcription, primarily usable via a Colab notebook.

Use cases

  • transcribe piano recordings to midi
  • convert multi-instrument audio into midi files
  • automatic music transcription from audio
  • extract notes from a song recording
  • transcribe audio files with pretrained model in colab

When to choose

  • you need audio-to-MIDI transcription of piano or multiple instruments
  • you want to use pretrained transcription checkpoints without training your own

When to avoid

  • you want to train or fine-tune a transcription model yourself, since training is not easily supported
  • you need a production-ready application or API rather than a research model

Facets

library · maturity maintenance

machine-learning deep-learning audio-processing nlp machine-learning artificial-intelligence python cloud music-transcription audio-to-midi transformers t5x multitrack ismir audio gpu

1 source

Member repositories

RepositoryRoleHealth v2
magenta/mt3main73

For agents

markdown · JSON · MCP: product_card(name="magenta/mt3")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem