Github Trends®
9802 findingsmedian surprise 0.00377window 7 days
UNIT / TREND-MONITOR · REV 2.6
[ 7 days window ]
SOURCE: own snapshots
FINDING #550 · UNIT ID 1290022584
perfectgf/lora-dataset-studio
Self-hosted, one-tab workbench for the whole LoRA lifecycle: build Character / Concept / Style datasets (generate from a reference, scrape, or triage a huge dump in the Image Bank), curate, caption, clean watermarks, train locally or in the cloud across five model families, then rank checkpoints in a Test Studio. Free & local.
[ PYTHON ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.0498
ENGAGEMENT0.36
FRESHNESS1.00
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
15% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D
2.86
ACCEL
+0.11
RETENTION
22.2%
PEAK 2026-07-28 · FORK-RETENTION 0.0% · 20 STARS / WINDOW

Author Audience

AUDIENCE
17
FOLLOWERS
5
OWNER ★
124

Engagement Signals

FORKS
18
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 20 / 20 (DIVERSITY 1.00)

Why This Is A Finding

perfectgf/lora-dataset-studio собрал 20 звёзд за окно, тогда как у автора всего 5 подписчиков — эффективная аудитория ≈ 17. Это даёт surprise-индекс 0.0498 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация положительная — рост ещё не выдохся.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9802 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.020.00+0.02ABOVE 94%
VELOCITY2.863.14-0.29ABOVE 45%
RETENTION22.2%20.0%+2.2 PPABOVE 51%
FORKS18210-192ABOVE 11%
SURPRISE0.050.00+0.05ABOVE 93%