onejune2018/Awesome-LLM-Eval
Awesome-LLM-Eval: a curated list of tools, datasets/benchmark, demos, leaderboard, papers, docs and models, mainly for Evaluation on LLMs. 一个由工具、基准/数据、演示、排行榜和大模型等组成的精选列表，主要面向基础大模型评测，旨在探求生成式AI的技术边界.
659
Stars
115
Forks
42.3
Radar Score
Stable
Momentum
Scoring Breakdown
Impact60.4
Velocity26.5
Health35.5
Growth Metrics
7-Day Stars
+0
30-Day Stars
+0
Acceleration
x
Language
—
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🛡️ Enterprise Readiness & Commercial Safety
Organic Growth
78%
Moderate Confidence
License
Permissive (Commercial Friendly)
Safe for commercial use, modification, and distribution.
Health Grade
C
Based on maintenance, issue response, and release cadence.
Radar Score
42.3
Composite of Impact, Velocity, and Health.
⚠️ Growth Anomaly Detected:
- Maintenance cadence: Last push 353 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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