OM
OpenGVLab/OmniQuant
[ICLR2024 spotlight] OmniQuant is a simple and powerful quantization technique for LLMs.
893 76 +0/wk
GitHub
large-language-models llm quantization
Trend
0
Star & Fork Trend (32 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
OpenGVLab/OmniQuant has +0 stars this period . Velocity data will be available after more historical data is collected.
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Signal-backed technical analysis will be available soon.
| Metric | OmniQuant | aidermacs | tutor-gpt | DISC-LawLLM |
|---|---|---|---|---|
| Stars | 893 | 893 | 893 | 894 |
| Forks | 76 | 72 | 93 | 90 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Python | Emacs Lisp | TypeScript | Python |
| Sources | 1 | 1 | 1 | 1 |
| License | MIT | Apache-2.0 | GPL-3.0 | Apache-2.0 |
Capability Radar vs aidermacs
OmniQuant
aidermacs
Maintenance Activity 27
Last code push 134 days ago.
Community Engagement 43
Fork-to-star ratio: 8.5%. Lower fork ratio may indicate passive usage.
Issue Burden 70
Issue data not yet available.
Growth Momentum 30
No measurable growth in the current period (first-day cold start expected).
License Clarity 95
Licensed under MIT. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.