Github Trends®
6512 findingsmedian surprise 0.00342window 3 days
UNIT / TREND-MONITOR · REV 2.6
[ 3 days window ]
SOURCE: own snapshots
FINDING #244 · UNIT ID 1308124634
FedericoTs/quantprobe
Run a 110B on a 2016 PC with 16 GB RAM. Know your tok/s before you download. Placement beats budget: predicts speed + memory fit for any GGUF on your exact hardware, self-calibrates, emits the exact llama.cpp command — or 'quantprobe auto' does it all. Falsification-tested laws; misses published at full size. pip install quantprobe
[ PYTHON ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.10
ENGAGEMENT0.52
FRESHNESS1.00
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
22% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D
5.33
ACCEL
+7.00
RETENTION
0.0%
PEAK 2026-08-08 · FORK-RETENTION 0.0% · 16 STARS / WINDOW

Author Audience

AUDIENCE
12
FOLLOWERS
5
OWNER ★
74

Engagement Signals

FORKS
6
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 16 / 16 (DIVERSITY 1.00)

Why This Is A Finding

FedericoTs/quantprobe собрал 16 звёзд за окно, тогда как у автора всего 5 подписчиков — эффективная аудитория ≈ 12. Это даёт surprise-индекс 0.10 (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 6512 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.050.00+0.05ABOVE 96%
VELOCITY5.335.330.00ABOVE 47%
RETENTION0.0%16.7%-16.7 PPABOVE 0%
FORKS6419-413ABOVE 4%
SURPRISE0.100.00+0.10ABOVE 96%