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Run your own model endpoint on a rented GPU with vLLM: your own API key, an SSH tunnel, and an optional LoRA adapter
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Run your own model endpoint on a rented GPU with vLLM: your own API key, an SSH tunnel, and an optional LoRA adapter

DEV Community: tutorial·CloudGPU·about 11 hours ago
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Short answer: rent a GPU with SSH access, install vLLM in a fresh Python environment, start it so it listens only on the instance's own localhost, require an API key of your own, and reach it from your machine through an SSH tunnel. If you have a LoRA adapter for the same base model, vLLM can serve it next to the base model under its own name. When you are done, copy out what you need and destroy the instance.

Disclosure: I work on CloudGPU, and the GPU rental in this guide is ours. Each step ends with a "What to check" line, because versions, flags and defaults change.

Which kind of endpoint is this?

CloudGPU's terms (section 6) say that each running instance with a service URL gets a public HTTPS address; these URLs are "hard to guess but they are not authenticated by default", and if you need authentication you configure it inside your instance, for example an API key on your Ollama deployment.…

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