1. linear issues I’ve been tinkering with coding agents for a few years now, and so far, they’ve felt burdened by the conceptual weight of their tools.
however, that’s been changing. primarily due to three things:
(1) they’ve been trained on tool traces, so they actually know when and how to call functions
(2) post‑training moved from pure ‘be helpful’ rlhf to reasoning‑centric feedback, verifier/unit‑test rewards, and scaled rl that favors planning and self‑correction)
github pypi phase prediction per best epoch
phasefinder is a beat estimation model that predicts metric position as rotational phase, heavily inspired by this paper. demos Your browser does not support the audio element. `are you looking up`
mk.gee Your browser does not support the audio element. `just the way it is`
action bronson Your browser does not support the audio element. `lethal weapon`
github pypi deeprhythm is a convolutional neural network designed for rapid, precise tempo prediction for modern music. it runs on anything that supports pytorch (I’ve tested ubuntu, macos, windows, raspbian).
audio is batch-processed using a vectorized harmonic constant-q modulation (hcqm), drastically reducing computation time by avoiding the usual bottlenecks encountered in feature extraction.
why? I needed a way to accurately estimate tempo that was small & fast enough run on a raspberry pi.