RollTab - AI autocomplete for piano on-device
Show HN: I trained a 125M model to autocomplete piano on-device
RollTab is a free iOS app that turns your MIDI piano into an AI-powered musical partner. Using a 125M-parameter transformer trained on MIDI data, it autocompletes your playing in real time, suggesting notes and chords that follow your style. The app runs entirely on-device, ensuring low latency and privacy. Built with a novel note-level tokenization and refined through direct preference optimization, RollTab offers a unique, responsive way to explore musical ideas and overcome creative blocks.
Think GitHub Copilot, but for piano.
- tom_vidal
This sort of “autocomplete” is actually fundamental to how classical composers were trained.
For anyone interested, I’d highly recommend reading Robert Gjerdingen’s article Gebrauchs-Formulas. https://www.researchgate.net/publication/259731561_Gebrauchs...
You can also listen to the transcript of four Russian composers, including Rachmaninoff, playing this pattern recognition and generation game at a dinner party in the late 1800’s: https://youtu.be/PlFPOWuwBHI?is=EKBK7QQkJs4MsTCU
Composers at the time could do this just by looking at sheet music and audiating, without using a piano.
- joshuamerrill
Classical pianist and software product designer here.
I see so much in common with this project and the numerous AI-based UX design tools out there. Whether it's music or UI, now that the "generation" portion of the work costs zero, all that remains is taste.
And so much of taste comes from exploring and killing off possibilities that turn out to be dead-ends. I love the idea that models like these will help us find the dead ends faster, or even produce a gem here and there.
P.S. if you want another uncanny version of Fur Elise, listen to Beethoven's own 1822 revision: https://www.youtube.com/watch?v=s24TtiGgb6k. His 1810 version that we all know was simpler and more balanced. But for what it's worth, Beethoven didn't publish either of them.
- jasonjmcghee
I think this is a great project and very HN. Not sure why the comments are so focused on the deliverable- you learned way more and had a much more interesting experience.
One think I didn't see mentioned in the post- maybe I missed it- how large was the data? How many samples did you use to pretrain and post-train
- karmelapple
Hearing the start of Für Elise, and then it being taken in an incredibly different direction, is surprisingly disconcerting.
- goda90
Reminds me of this project to generate every melody possible algorithmically in order to fight music copyright lawsuits.
- ghm2199
Interesting. I do feel letting a machine generating notes is taking the joy out of improvisation, is it not?
I think one of the great, early, joys of learning a piano is gaining the following intuitions: The seemingly harder path of learning sheet is actually faster. Your mind _should_ learn to think in two dimensions Spatial — where fingers go — and Time — pitch and tempo – ** when learning. The _internalization_ of Space and Time queues guide the fingers in a dance that is vastly satisfying. This skill leads you to the final part of the journey that is improvisation and the one more exciting than what i am on now.
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**
Space: Your finger placement on keys right, e.g. knowing how to go from landmark/anchor notes(mid-c, G, F etc) and then go to the others above and below it. Crudely this is some what like typing from your landmark f and j qwerty keyboard
Time: The out singing/verbalizing of the notes/beats on a time measure as you play them(per the time measure). e.g. you can say out loud 1-2-3-4 for 4/4 measure, if the measure has quarter notes say out loud. And `1-e-and-a-2-e-and-a-3-e-and-a-4-e-and-a` for a 4/4 with 1/16th note granularity. Do this as you play the notes and you get a sense of tempo.
- mare5x
Really cool! It reminds me of a demo I saw live at NeurIPS: https://www.youtube.com/watch?v=8s3V922h3CU (paper at https://openreview.net/pdf?id=3yeBer3J5z).
If you like such creative AI work, I would recommend looking at the other "NeurIPS Creative AI Track 2025" submissions as well.
- timmb
Reminds me of Francois Pachet’s Continuator (all the way back in 2003, using hierarchical markov models)