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Found 3 Skills
Deploy GPU workloads to RunPod serverless and pods - vLLM endpoints, A100/H100 setup, scale-to-zero, cost optimization. Use when: deploy to RunPod, GPU serverless, vLLM endpoint, scale to zero, A100 deployment, H100 setup, serverless handler, GPU cost optimization.
Deploying and hosting a Serverpod server, with Serverpod Cloud as the default. Use when the user asks how to deploy, ship, host or run their server in production. Deploying is the user's decision, not something to carry out for them.
Provision a Runpod Pod for interactive, development or training use and tell the user exactly how to connect to it. Reads stock before creating, picks the image and GPU class from the catalog reads, exposes only the ports the workload needs, hands back the working proxy URL or SSH address, and for training co-locates a network volume so checkpoints outlive the Pod. Also covers creating a Pod and stopping it immediately, so that only its disk bills until the user comes back. Use when the user wants a GPU or CPU machine of their own (a web app, Jupyter, SSH, a training box) rather than a Serverless endpoint, through the Runpod MCP tools.