EDM-98 + EDMFormer on PyPI: Run AI Inference Without the Setup Pain (NexaAPI Tutorial)

A new ML package just dropped on PyPI — edm98 — bringing the EDM-98 dataset and EDMFormer inference tooling to Python developers. Here's what it is, why it matters, and how to build with it today — without the setup headache. What Is EDM-98? EDM-98 is a curated dataset of 98 Electronic Dance Music tracks, labeled with structural segments using Rekordbox cue-point annotations. Each track is tagged with sections like: intro — the opening section buildup — rising energy before the drop drop — the peak energy section breakdown — the quiet middle section outro — the closing section silence — gaps between sections The edm98 Python package bundles this dataset with an EDMFormer -based inference pipeline — a transformer model that can predict song structure from audio embeddings. from edm98.loaders import load_dataset_records , load_all_splits # Load the canonical dataset records = load_dataset_records () splits = load_all_splits () # Example record print ( records [ 0 ]) # { # "id": "10605643