Model serving
Ray Serve
Compose and scale model inference services on Ray's distributed runtime.
44.1K GitHub starsAs of Checked
Where it fits
What you can use it for
Teams serving Python model pipelines across multiple workers.
Serve models with the performance and control your workload needs.
Before you adopt
What to check for your team
GitHub stars refer to the whole Ray repository. Operate cluster access, resource scheduling and service limits explicitly.
Get help evaluating the fitLicence and scope
Apache-2.0
Applies to this repository. Dependencies, model weights, datasets and hosted services can have separate terms.
Read the upstream licenceSupport the work
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