Hugging Face trending models (agent-curated)
Weekly popularity-velocity ranking of trending models on the Hugging Face Hub. Two sweeps of the official keyless Hub API (https://huggingface.co/api/models), one sorted by likes and one by downloads (top 2 pages each), are merged and deduped on model id. Each model carries its license tag normalized to a canonical id (informational, not legal advice), its pipeline tag normalized to a coarse modality (text, vision, audio, video, multimodal, other, unknown), and author/name parts. Popularity velocity is likes and downloads per day since model creation (age floored at 1 day); the trend_score is a documented 0-100 composite = 50% min-max-normalized likes/day + 50% min-max-normalized downloads/day, and trend_rank orders by trend_score descending (ties: likes desc, then model id). Columns: ISO week, fetch timestamp, model id / URL / author / name, pipeline tag, library name, modality, normalized license id, comma-joined tags, likes, downloads, creation timestamp, age in days, likes/day, downloads/day, trend score (0-100), trend rank. Primary key: (week, model_id). Cadence: weekly. Nullability: pipeline_tag, library_name and license_spdx may be empty when the author supplied none; likes, downloads, trend_score and trend_rank are never null. Caveats: likes/downloads are cumulative totals, so per-day rates are lifetime averages, not trailing-week gains; the rank therefore favors models with sustained momentum as well as fast risers; license_spdx comes from author-applied tags and may be missing or wrong — verify before use; popularity is not quality. Sample use: order by trend_rank for the week's hottest models, or filter modality = 'vision'.
- machine-learning
- huggingface
- technology
- signals