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SkillsMP has collected 7 skills from wikimedia/machinelearning-liftwing-inference-services. Open a skill to review its source and details.
Showing 7 of 7 collected skills.
Triage Wikimedia ML inference-services incidents at a time T (now or past). TRIGGER on "investigate / triage / debug / post-mortem / what happened" when the subject is a LiftWing alert, ML-serve namespace, error spike, latency regression, or pod crash —…
Analyze a model server's Python code and its deployment chart to identify performance bottlenecks and optimization opportunities for CPU and GPU (AMD MI300X, ROCm, vLLM) inference services on KServe. Use when you want to improve inference throughput or…
Scaffold a new LiftWing ML service in operations/deployment-charts. Handles both adding to an existing namespace (append inference_services entry) and creating a brand-new namespace (full helmfile scaffold). Use when an engineer wants to deploy a new…
Bump the Docker image tag for one or more LiftWing inference services in operations/deployment-charts after a new image is published by Jenkins. Use when a patch has merged in inference-services, PipelineBot has posted a new image tag on the Gerrit CL, and…
Help pinpoint why a Wikimedia ML KServe/Knative InferenceService deployment is not working on ml-serve or ml-staging Kubernetes clusters.
Build and run a model server locally via Docker Compose, then test it with curl. Use when the engineer wants to test a model server locally before committing.
Scaffold a new KServe model server from scratch — create the model.py, Blubber config, Docker Compose service, pipeline config, and CI wiring. Use when the engineer wants to add a new inference service model to this repo.