zhezhaoa/ngram2vec
Four word embedding models implemented in Python. Supporting arbitrary context features
848
Stars
171
Forks
47.4
Radar Score
Stable
Momentum
Scoring Breakdown
Impact70.7
Velocity29.6
Health35.0
Growth Metrics
7-Day Stars
+0
30-Day Stars
+0
Acceleration
x
Language
Python
Why it ranks
Modest but positive momentum.
Top 46% globally
🛡️ Enterprise Readiness & Commercial Safety
Organic Growth
79%
Moderate Confidence
License
Unlicensed / Custom
Review license terms carefully before commercial adoption.
Health Grade
C
Based on maintenance, issue response, and release cadence.
Radar Score
47.4
Composite of Impact, Velocity, and Health.
⚠️ Growth Anomaly Detected:
- Maintenance cadence: Last push 2639 days ago.
Disclaimer: This is an automated heuristic assessment based on public GitHub signals. Always perform your own security audit, dependency review, and legal compliance check before production deployment.
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