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Open-weight model

amtflow

by Vaclis vaclis/amtflow

amtflow is an open-weight model from Vaclis, released under Creative Commons Attribution 4.0. Its published files total 45.1 MB.

Model assets for AMTFlow, a modular instrument-conditioned automatic music transcription pipeline (instrument tagging → instrument-family routing → MuScriptor). AMTFlow downloads these files on first use; you do not need to fetch them by hand.

Parameters—
Context—
Weights45.1 MB
Licensecc-by-4.0
AccessOpen weights
Monthly Downloads—

Model Card

By Vaclis, published under cc-by-4.0, revision 1e9418469645.

Model assets for AMTFlow, a modular instrument-conditioned automatic music transcription pipeline (instrument tagging → instrument-family routing → MuScriptor). AMTFlow downloads these files on first use; you do not need to fetch them by hand. One classification head per frozen audio encoder, trained on OpenMIC-2018 (20 instrument classes). AMTFlow's probe tagger runs the encoder, applies the head to one layer's time-averaged features, and marks an instrument family present when any of its classes reaches that class's threshold. Several taggers, including audio-language models, can be combined by union or majority vote. Test mAP is the mean over five probe seeds with a 95% t-interval over…

Read Vaclis's full model card

Model assets for AMTFlow, a modular instrument-conditioned automatic music transcription pipeline (instrument tagging → instrument-family routing → MuScriptor). AMTFlow downloads these files on first use; you do not need to fetch them by hand.

heads/openmic/ — instrument-tagging heads

One classification head per frozen audio encoder, trained on OpenMIC-2018 (20 instrument classes). AMTFlow's probe tagger runs the encoder, applies the head to one layer's time-averaged features, and marks an instrument family present when any of its classes reaches that class's threshold. Several taggers, including audio-language models, can be combined by union or majority vote.

head encoder layer OpenMIC test mAP macro-F1
openmic/af3-whisper-mlp nvidia/audio-flamingo-3-hf audio tower 31 0.861 ± 0.001 0.793
openmic/afnext-whisper-mlp nvidia/audio-flamingo-next-hf audio tower 29 0.860 ± 0.003 0.788
openmic/matpac-music-mlp auriankelen/matpac_music 10 0.860 ± 0.002 0.792
openmic/matpac-general-mlp auriankelen/matpac_general_audio 10 0.858 ± 0.002 0.787
openmic/pupum2d-mlp spellbrush/PupuM2D (large) 19 0.858 ± 0.001 0.790
openmic/muq-mlp OpenMuQ/MuQ-large-msd-iter 2 0.832 ± 0.001 0.764
openmic/qwen3-omni-aut-mlp Qwen/Qwen3-Omni-30B-A3B-Instruct AuT encoder 23 0.821 ± 0.001 0.753
openmic/mert-mlp m-a-p/MERT-v1-330M 9 0.818 ± 0.002 0.740

Test mAP is the mean over five probe seeds with a 95% t-interval over seeds (the file is the best-validation seed). For reference, the MATPAC++ authors' released OpenMIC probe scores 0.861 on the same test clips.

Protocol. Official split01 test partition (5,085 clips); the official train partition split 80/20 by track (seed 0) into train/validation. Labels: aggregated relevance ≥ 0.5 is positive; unobserved (clip, class) labels are masked out. Every encoder layer is averaged over the 10 s clip and z-scored on train; the head is an MLP (512 hidden, ReLU, dropout 0.2) trained with masked BCE; layer and learning rate are selected on validation mAP. Per-class thresholds are calibrated on validation by F-beta (β = 2, precision ≥ 0.25), i.e. recall-oriented, because the transcriber cannot produce an instrument outside its conditioning set.

Files. <encoder>-mlp.safetensors holds the head weights and the train-set feature mean/std; its metadata (amtflow key, JSON) holds the encoder, layer, class names, thresholds and calibration details. index.json lists every head with its test scores and SHA-256.

License

The heads are released under CC BY 4.0 (OpenMIC-2018 is CC BY 4.0). A head is only usable together with its encoder, and the encoder's own license applies: MATPAC++ (Apache-2.0), PupuM2D (MIT), Qwen3-Omni (Apache-2.0), MERT and MuQ (CC BY-NC 4.0), Audio Flamingo 3 / Next (NVIDIA non-commercial). MuScriptor, the transcriber AMTFlow uses, is CC BY-NC 4.0.

Citation

AMTFlow is the transcription pipeline of the MIDI-REPA paper. If you use it, please cite:

@misc{yu2026midirepa,
      title={MIDI-REPA: Improving Text-to-Music Generation with Symbolic Representation Alignment},
      author={Song-Ze Yu and Fang-Duo Tsai and Yi-Hsuan Yang},
      year={2026},
      eprint={2610.20967},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2610.20967},
}

Identity and Version

Repository
vaclis/amtflow
Publisher
Vaclis
Task
Not stated by the source
Modality
Other
Library
amtflow
Parameters
Not stated by the source
Languages
Not stated by the source
Revision
1e94184696459f43efa6b87785c771d3e1653914
First published
2026-09-29
Last updated
2026-10-16

Files and Weights

11 files, 45.1 MB in total. The weights are 8 files totalling 45.1 MB in safetensors.

Weights8 files · 45.1 MB
Configuration1 file · 8.4 KB
Documentation1 file · 4.2 KB
Repository1 file · 1.5 KB
Every file
FileTypeSizeSHA-256
heads/openmic/af3-whisper-mlp.safetensorsWeights2.7 MB a90b7c832ee3
heads/openmic/afnext-whisper-mlp.safetensorsWeights2.7 MB 9c73f445d079
heads/openmic/matpac-general-mlp.safetensorsWeights7.9 MB 2b02dfaa07b3
heads/openmic/matpac-music-mlp.safetensorsWeights7.9 MB 45368f57df0b
heads/openmic/mert-mlp.safetensorsWeights2.2 MB 0e2f7079312e
heads/openmic/muq-mlp.safetensorsWeights2.2 MB 491768d02912
heads/openmic/pupum2d-mlp.safetensorsWeights16.9 MB 910b619fa5b2
heads/openmic/qwen3-omni-aut-mlp.safetensorsWeights2.7 MB d5b7ccbb0916
heads/openmic/index.jsonConfiguration8.4 KB —
README.mdDocumentation4.2 KB —
.gitattributesRepository1.5 KB —

License and Download

License
cc-by-4.0
Access
Open weights, no gate
Download size
45.1 MB
Download from Vaclis

Released by Vaclis through its official repository on Hugging Face. Read the license.

Built From

  • Described by arXiv:2610.20967
  • Trained on (disclosed) openmic-2018

Memory Requirements

PrecisionWeights in memory
As published45.1 MB

Weights only, from the published parameter count; the key-value cache and runtime add to this.

Questions About amtflow

Can I use amtflow commercially?

Yes. amtflow is released under Creative Commons Attribution 4.0. CC BY 4.0 permits sharing and adapting the work, including commercially, provided the creator is credited and changes are indicated.