eustlb/audio-classification-models-on-the-hub
Number of audio classification models on the Hub
Every public model repo currently tagged audio-classification on the Hugging Face Hub, counted by the month it was created, with landmark releases pinned along the timeline as their lab's logo.
Hover a column for that month's figures, or click it to keep the box open. Hover a logo for the model; click it to open the repo on the Hub. Hovering a column gathers that month's logos underneath it.
Nothing runs on the Hub: this is a static Space, so no hardware is assigned and no container is started. The browser renders a page built ahead of time, and the figures sit in it as two <script type="application/json"> blocks.
Files
Staying current
A single scheduled Hugging Face Job refreshes every audio-task Space in this family, this one included. It pulls each Space, re-reads the Hub API, rebuilds, and pushes back only files whose bytes changed — so a quiet day leaves no commit.
python3 refresh.py # or run it by handHow landmarks are chosen
Ranked by likes, which is the only engagement signal the listing API returns, then filtered twice: repos that repackage another team's weights (GGUF, ONNX, MLX, quantisations) are dropped as formats rather than releases, and one owner may hold at most four slots so a single lab cannot crowd out the field. A pins.json, where present, is a hand-curated list merged in ahead of those.
Caveats
This is a survivorship count. The Hub API returns only models that exist today and carry the tag now. Repos deleted since, or created under another tag and retagged later, are invisible, so early months are understated.
The window starts at 2022-04 — it 2022-03 is the Hub's createdAt backfill, not activity: 75-100% of it lands on 2022-03-02 across hundreds of unrelated owners, so those repos predate the field. Cumulative figures in the hover box still count from the true start of the series.
Landmark figures are all-time, so older releases have had longer to accumulate downloads and likes than recent ones.
