intel/auto-round
PTQ-Level Efficiency, QAT-Level Accuracy | 训练后量化的效率，量化感知训练的精度
1.7k
Stars
201
Forks
60.6
Radar Score
Rising
Momentum
Scoring Breakdown
Impact72.0
Velocity47.6
Health60.5
Growth Metrics
7-Day Stars
+0
30-Day Stars
+0
Acceleration
x
Language
Python
Why it ranks
Steady growth — consistently collecting stars and contributors.
LLM Frameworks · inference engineTop 23% globally
Popular Alternatives & Competitors
Top projects in the same category (LLM Frameworks) — compare side by side.
🛡️ Enterprise Readiness & Commercial Safety
Organic Growth
99%
High Confidence
License
Permissive (Commercial Friendly)
Safe for commercial use, modification, and distribution.
Health Grade
A
Based on maintenance, issue response, and release cadence.
Radar Score
60.6
Composite of Impact, Velocity, and Health.
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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