Model weights flow from registry to a shared GPU in a KitOps explainer
687 views·23 likes·5 saves·3 reposts·Posted 27 Sept 2026 · 0:30 · Explainers
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A 30-second technical explainer showing a model packaged as a KitOps ModelKit, pulled from an OCI registry by an init container, scheduled onto a controlled GPU share by HAMi and served through SGLang as an API.
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So impressed with the Opus 5.5 explainer videos - Here's another one - Serve Models from a @Kit_Ops ModelKit on @HAMiProject Detailed explanation of how Your model is packaged as a versioned ModelKit. KitOps pulls it from an OCI registry and unpacks it inside the Pod. HAMi schedules a controlled GPU share. SGLang loads the model locally and serves an OpenAI-compatible API. One clear path from model artifact to working inference. KitOps and HAMi.
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