OM
NVlabs/OmniVinci
OmniVinci is an omni-modal LLM for joint understanding of vision, audio, and language.
652 51 +0/wk
GitHub
audio-language-model deep-learning large-language-models multimodal-large-language-models vision-language-model
Trend
3
Star & Fork Trend (21 data points)
Stars
Forks
Multi-Source Signals
Growth Velocity
NVlabs/OmniVinci has +0 stars this period . 7-day velocity: 0.3%.
Deep analysis is being generated for this repository.
Signal-backed technical analysis will be available soon.
| Metric | OmniVinci | self-supervised-depth-completion | bayesflow | pysentimiento |
|---|---|---|---|---|
| Stars | 652 | 652 | 651 | 651 |
| Forks | 51 | 134 | 82 | 72 |
| Weekly Growth | +0 | +0 | +0 | +0 |
| Language | Python | Python | Python | Jupyter Notebook |
| Sources | 1 | 1 | 1 | 1 |
| License | Apache-2.0 | MIT | MIT | NOASSERTION |
Capability Radar vs self-supervised-depth-completion
OmniVinci
self-supervised-depth-completion
Maintenance Activity 80
Last code push 42 days ago.
Community Engagement 39
Fork-to-star ratio: 7.8%. 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 Apache-2.0. Permissive — safe for commercial use.
Risk scores are computed from real-time repository data. Higher scores indicate healthier metrics.