Datasets:

modelpulse
/

model-pulse-data

license: apache-2.0
pretty_name: Model Pulse — daily history of Hugging Face models, datasets and Spaces
tags:
  - hub-stats
  - downloads
  - time-series
size_categories:
  - 100M<n<1B
configs:
  - config_name: series
    data_files: series/*.parquet
  - config_name: models
    data_files: models.parquet
  - config_name: family_series
    data_files: family_series/*.parquet
  - config_name: author_series
    data_files: author_series/*.parquet
  - config_name: hub_series
    data_files: hub_series.parquet
  - config_name: dataset_series
    data_files: datasets/series/*.parquet
  - config_name: datasets
    data_files: datasets/datasets.parquet
  - config_name: space_series
    data_files: spaces/series/*.parquet
  - config_name: spaces
    data_files: spaces/spaces.parquet
  - config_name: uses
    data_files: uses.parquet

Model Pulse data

Daily download and like history for every actively used model and dataset on the Hugging Face Hub, and daily likes for every liked Space, from 2024-07-29 onward, updated every day. It powers Model Pulse, also at modelpulse.ifsp.dev with a page for every model, dataset and Space.

Built from the daily snapshots of cfahlgren1/hub-stats (Apache 2.0), reading each historical revision of models.parquet, datasets.parquet and spaces.parquet.

Files

Path	Rows	What it holds
`series/YYYY-MM.parquet`	one per model per snapshot day	`id, day, dl30, dl_all, likes`
`models.parquet`	one per tracked model	latest metadata plus derived metrics (`dl_7d`, `growth_7d`, ranks, family totals)
`children.parquet`	one per base→derivative edge	direct derivatives with relation and downloads
`family_series/YYYY-MM.parquet`	one per base model per day	downloads summed over the model and all its derivatives
`author_series/YYYY-MM.parquet`	one per author per day	downloads summed over the author's models
`hub_series.parquet`	one per day per task	Hub-wide daily downloads by `pipeline_tag`
`leaderboards.json`		weekly rankings shown on the site
`datasets/series/YYYY-MM.parquet`	one per dataset per snapshot day	`id, day, dl30, dl_all, likes`
`datasets/datasets.parquet`	one per tracked dataset	latest metadata (task, size, license) plus derived metrics and usage counts
`datasets/author_series/`, `datasets/hub_series.parquet`, `datasets/leaderboards.json`		the same views as for models
`spaces/series/YYYY-MM.parquet`	one per Space per snapshot day	`id, day, likes, trending`
`spaces/spaces.parquet`	one per Space with at least one like	title, emoji, SDK, likes gained in 7 and 30 days, ranks
`spaces/new_by_sdk.parquet`	one per day per SDK	Spaces created each day, from the latest snapshot
`uses.parquet`	one per reference	`src_kind, src, dst_kind, dst, created, weight`: a Space using a model or dataset, or a model trained on a dataset, from today's cards
`repos_meta.json`		days covered and skipped snapshots for datasets and Spaces

Notes

dl30 is the Hub's rolling 30-day download count. dl_all (all-time downloads) only exists from 2025-02-27, so exact daily downloads, computed as the difference of dl_all between snapshots, start on that date.
Some days are missing in the source (Aug 2024, Jun 2025, Apr 2026, May–Jun 2026). Totals are unaffected; daily values across a gap are averages.
A model or dataset is tracked once it has 10+ downloads in 30 days, 50+ all-time downloads, or at least one like. A Space is tracked once it has a like; the Hub doesn't publish visits for Spaces.
On some days the Hub's download counters stand still and catch up a day or two later, mostly on Wednesdays. Dataset counters freeze all at once; model counters often freeze only in part (newer repos stop, older ones keep counting), so the model total may only dip to half. A day is treated as a stall when the total is under 0.3 of its 15-day median, when at least 25% of the models with 60K+ monthly downloads didn't move at all, or when a dip under 0.7 is made up by the next or previous day. hub_series spreads each episode evenly over its days (sums unchanged), and the snapshots inside it are listed in skip_days (meta.json for models, repos_meta.json for datasets) so per-repo series can do the same. frozen in the same files holds the recent daily share of frozen counters.
Twice (May 2025, June 2026) the all-time counters went down for a large share of models and came back days later. Those snapshots are in skip_days too, and downloads across them are measured from the last good snapshot to the first one after the counters recovered, so the recovery isn't counted as new downloads. A drop that doesn't recover within 8 snapshots is treated as a lasting correction by the Hub, not set aside.
uses.parquet comes from the cards as they are today, dated by when each Space or model was created, not by when it started using what it lists.
Download counts follow the Hub's counting rules; the Hub occasionally books delayed downloads on a single day.