HandsOnLLM/Hands-On-Large-Language-Models — GitHub trend

◂ BACK TO LEADERBOARD

FINDING #948 · UNIT ID 821372392

HandsOnLLM/Hands-On-Large-Language-Models

Official code repo for the O'Reilly Book - "Hands-On Large Language Models"

[ JUPYTER NOTEBOOK ][ ORG ][ GITHUB ↗ ]

SURPRISE SCORE

0.00

Score Breakdown

SURPRISE0.000441

ENGAGEMENT0.65

FRESHNESS1.33

SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE

SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)

2% OF STARS IN ARCHIVE

Growth Telemetry

VELOCITY /D

3.42

ACCEL

-0.07

RETENTION

2.7%

PEAK 2026-03-15 · FORK-RETENTION 68.2% · 616 STARS / WINDOW

Author Audience

AUDIENCE

7,715

FOLLOWERS

985

OWNER ★

28,724

Engagement Signals

FORKS

6,591

ISSUE AUTH

PR AUTH

UNIQUE STARGAZERS 615 / 616 (DIVERSITY 1.00)

Why This Is A Finding

HandsOnLLM/Hands-On-Large-Language-Models собрал 616 звёзд за окно, тогда как у автора всего 985 подписчиков — эффективная аудитория ≈ 7,715. Это даёт surprise-индекс 0.000441 (звёзды относительно охвата автора, а не в абсолюте). Удержание форков 68.2% и 4 внешних контрибьюторов отделяют реальный инструмент от разовой вспышки. Акселерация отрицательная — внимание остывает после пика.

Related Findings

RANKS ABOVE 44% OF 1696 FINDINGS

#229duoan/TorchCode[ JUPYTER NOTEBOOK ]0.00437 #458Lordog/dive-into-llms[ JUPYTER NOTEBOOK ]0.00195 #480tkarim45/Beginner-Data-Science-Projects[ JUPYTER NOTEBOOK ]0.00188 #576gepa-ai/gepa[ JUPYTER NOTEBOOK ]0.00139 #711lyogavin/airllm[ JUPYTER NOTEBOOK ]0.000888

METRICS IN CONTEXT

MEDIAN ACROSS ALL 1696 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW

METRICVALUEMEDIANΔ MEDPERCENTILE

SCORE0.000.00-0.00ABOVE 44%

VELOCITY3.422.82+0.60ABOVE 60%

RETENTION2.7%4.8%-2.1 PPABOVE 26%

FORKS6,5911,584+5,008ABOVE 84%

SURPRISE0.000.00-0.00ABOVE 44%