Deploy your own AI model on your own cloud GPU

I deployed an OpenWhate AI model to the cloud, exposed it through an API, and connected it to a Python application.

And in this video, I'm gonna walk you through the end-to-end demonstration and show you how you can implement same for your business.

So what this command would do is to deploy the model, set up all these configurations that I just explained that we have set up in the Python script here, and then return HTTPS API endpoint.

From model, which becomes like the gateway of talking to our AI model.

So as you can see, it just finished running and you can see the API endpoint here.

You can see that the API response status is 200, showing that it was successful.

That's green.

And more importantly, you can see the token usage.

The prompt token that I sent was 38 tokens and the AI model responded with 88 tokens.

Authorized clients can access the model whilst unauthorized clients, their requests are rejected.

So at DomainOS, what we offer is managed inference service, where we essentially help organizations to deploy and operate their open-weight AI models behind APIs that they control, with deployment configurations that are tailored to their requirements.