Github Trends®
9314 findingsmedian surprise 0.00458window 3 days
UNIT / TREND-MONITOR · REV 2.6
[ 3 days window ]
SOURCE: own snapshots
FINDING #1617 · UNIT ID 1335460253
Greninja9257/LabLLM
A native macOS lab for teaching tiny language models to think — build the architecture, train the weights, and watch a small LLM emerge from scratch, locally on Apple Silicon with custom data, tokenizers, checkpoints, and MLX acceleration.
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.0922
ENGAGEMENT0.0533
FRESHNESS1.00
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
19% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D
4.67
ACCEL
-0.00
RETENTION
90.0%
PEAK 2026-08-23 · FORK-RETENTION 0.0% · 14 STARS / WINDOW

Author Audience

AUDIENCE
11
FOLLOWERS
0
OWNER ★
108

Engagement Signals

FORKS
1
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 14 / 14 (DIVERSITY 1.00)

Why This Is A Finding

Greninja9257/LabLLM собрал 14 звёзд за окно, тогда как у автора всего 0 подписчиков — эффективная аудитория ≈ 11. Это даёт surprise-индекс 0.0922 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 0.0% и 0 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

METRICS IN CONTEXT

MEDIAN ACROSS ALL 9314 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.010.00+0.01ABOVE 83%
VELOCITY4.675.67-1.00ABOVE 39%
RETENTION90.0%40.0%+50.0 PPABOVE 91%
FORKS1324-323ABOVE 3%
SURPRISE0.090.00+0.09ABOVE 92%