Decomposer decompiles symbolic music (MIDI) into executable Strudel programs.
This model is the 8B model from the paper Decomposer: Learning to Decompile Symbolic Music to Programs, post-trained from Qwen3-8B.
Header[BPM=… Meter=…] — tempo/meter; if absent, madmom is used to estimate them.
Events — one line per instrument, pitch@cycle_onset tokens; melodic pitches as note
names (C4, F#3), drums as GM drum names (bass_drum, closed_hi_hat).
Training Data
Strudel-Synth is a synthetic corpus of 21,174 (MIDI, Strudel) pairs
(20,152 train / 1,022 test) built by distilling Strudel programs from Claude-Opus-4.6
and rendering each to MIDI with the Strudel runtime. Its ~20K training split is divided
into two disjoint ~10K halves, one per stage:
SFT uses the first half as paired (MIDI, Strudel) examples.
RL uses the second half (MIDI only), plus short-fragment (<30 s) LMD MIDI.
Inference Hyperparameters
Recommended settings matching the paper evaluation:
Setting
Value
temperature
1.0
max_new_tokens
4096
enable_thinking
false
Citation
If you find our model useful, please cite our research as
bibtex
1@article{kim2026decomposer,
2 title = {Decomposer: Learning to Decompile Symbolic Music to Programs},
3 author = {Kim, Yewon and Gandhi, Apurva and Chung, David and Neubig, Graham and Donahue, Chris},
4 journal = {arXiv preprint arXiv:2607.01849},
5 year = {2026}
6}