π₯ SoftChart v1.5 β unified model
One 7.94M-parameter model (bf16, ~16 MB) replacing three (slot generator + time generator + beat model, 24.5M / ~98 MB): β68% parameters, β84% disk, with measured quality parity or better on every axis.
| axis | v1.5 (this model) | v1.0 dedicated | verdict |
|---|---|---|---|
| slot-mode F1 (12 songs) | 0.663 / oni 0.732 | 0.665 / 0.727 (slot12) | parity, oni better |
| time-mode F1 | 0.682 / oni 0.721 | 0.659 (pr12) | better |
| beat grid ok-rate (const) | 1.0 Β· p50 10.5 ms | 0.93 Β· 10.2 ms (beatd2) | better |
| beat grid (variable BPM) | 0.9 Β· p50 3.2 ms | 1.0 Β· 4.0 ms | parity |
| tuplet evenness (CV) | 0.0006 | 0.0006 | parity |
How the reduction was achieved (all measured, see repo REPORT):
- Role folding β dual-mode training (50% slot / 50% time windows, MODE token) + a hi-res beat head. Beat supervision is masked on slot windows: they carry grid-phase input channels, and an unmasked head copies the channels instead of listening (measured collapse: 723 ms β fixed: 10.5 ms).
- Factorized embeddings (ALBERT-style, E=64) β position tokens are 95% of the table; 463K β 132K.
- bf16 weights β training ran bf16 autocast, so fp32 storage carried no extra information (verified: F1/grid identical within noise).
Interesting side effect: the shared trunk improved both the time mode (+2.3pp over the dedicated model) and the beat ok-rate β beat supervision appears to act as a metrical regularizer for generation, and vice versa.
Usage (drop-in for all three v1.0 roles):
from softchart.generate import load_hf, generate_song_slot, generate_song
from softchart.grid import fit_grid_piecewise
from softchart.tja import write_tja_slots
m = load_hf("JacobLinCool/softchart-v15") # one model, three roles
grid = fit_grid_piecewise(m, mel) # its own beat head drives the grid
g = generate_song_slot(m, mel, grid, "oni", level=9, density_bucket=7)
tja = write_tja_slots(g, grid, "Title", "oni", 9, "song.ogg")
# gridless fallback: generate_song(m, mel, "oni", level=9) (time mode)
MIT-licensed. Trained from scratch on community-made charts (taiko-1000-parsed); the official game never released chart data.
- Downloads last month
- -
Inference Providers NEW
This model isn't deployed by any Inference Provider. π Ask for provider support