Package · PyPI
PyPI · v0.30.0 · Apache-2.0
A framework for efficient model inference with omni-modality models
Tentative categories were assigned with moderate confidence (0.5 to 0.75): they are shown, but they do not count toward a category’s momentum. How categories work
pip install vllm-omniPyPI publishes no adoption figure, so there is no growth to derive. Nothing is estimated in its place.
Adoption history
PyPI publishes no adoption count, so there is no history to chart. That is a fact about the registry, not a gap in ours: the package’s releases and maintenance are measured instead.
In the Crest catalog
A framework for efficient model inference with omni-modality models
Linked by the package’s own registry metadata.GitHub (opens in a new tab)
==1.12.0==3.1.16>=14.0.0==1.5.0>=0.3.1==0.40.0>=0.8.1==0.0.3>=0.10.0>=2.37.2>=1.0.0==0.16.1>=1.0.0>=2.3.0>=1.23.2>=20250625>=3.8.0>=2.1.0>=2.0.0>=25.0.0==0.3.0>=0.8.0>=1.11.0>=0.13.1>=0.5.0.post1>=0.2.6>=4.66.0<5.15,>=5.13.0>=2.12.2No published news event mentions this package or its repository yet.