Github Trends®
8038 findingsmedian surprise 0.00514window 3 days
UNIT / TREND-MONITOR · REV 2.6
[ 3 days window ]
SOURCE: own snapshots
FINDING #7477 · UNIT ID 1172198295
duoan/TorchCode
🔥 LeetCode for PyTorch — practice implementing softmax, attention, GPT-2 and more from scratch with instant auto-grading. Jupyter-based, self-hosted or try online.
[ JUPYTER NOTEBOOK ][ GITHUB ↗ ]
SURPRISE SCORE
0.00

Score Breakdown

SURPRISE0.00553
ENGAGEMENT0.31
FRESHNESS1.00
SCORE = SURPRISE × ENGAGEMENT^0.7 × FRESHNESS × VISIBILITY × CONFIDENCE
SURPRISE = WINDOW STARS / DAYS / (AUDIENCE + FLOOR)
0% OF STARS IN ARCHIVE
[BOT] SUSPECTED STAR BOT — SCORE PENALIZED. SIGNATURES:
S2 · NO EXTERNAL ISSUE/PR AUTHORS DESPITE 100+ STARS
S10 · DEAD CODE, ZERO CONTRIBUTORS, YET STARS KEEP DRIPPING

Growth Telemetry

VELOCITY /D
4.67
ACCEL
+1.50
RETENTION
0.0%
PEAK 2026-10-12 · FORK-RETENTION 0.0% · 14 STARS / WINDOW

Author Audience

AUDIENCE
805
FOLLOWERS
235
OWNER ★
5,695

Engagement Signals

FORKS
413
ISSUE AUTH
0
PR AUTH
0
UNIQUE STARGAZERS 14 / 14 (DIVERSITY 1.00)

Why This Is A Finding

duoan/TorchCode собрал 14 звёзд за окно, тогда как у автора всего 235 подписчиков — эффективная аудитория ≈ 805. Это даёт surprise-индекс 0.00553 (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 8038 FINDINGS · Δ vs MEDIAN · PERCENTILE = SHARE RANKED BELOW
METRICVALUEMEDIANΔ MEDPERCENTILE
SCORE0.000.00-0.00ABOVE 7%
VELOCITY4.675.67-1.00ABOVE 38%
RETENTION0.0%14.3%-14.3 PPABOVE 0%
FORKS413333+81ABOVE 54%
SURPRISE0.010.01+0.00ABOVE 51%