You can add the power of a VM running on your own server to a https://CoCalc.com project.
VIDEO: https://youtu.be/NkNx6tx3nu0
Open a project on https://cocalc.com, then create a Jupyter notebook with the Python kernel and do some basic computations. You can then add a compute server to your project and instead run the notebook temporarily on the compute server. E.g., in the video I add an on-prem compute server running on my Macbook Pro laptop to a CoCalc (https://cocalc.com) project, and using the compute server via a Jupyter notebook and a terminal. This involves creating an Ubuntu 22.04 virtual machine via multipass, and pasting a line of code into the VM to connect it to CoCalc.
After using a compute server running on my laptop, I create another compute server running on Lambda cloud (https://lambdalabs.com/). This involves renting a powerful server with an H100 GPU, waiting a few minutes for it to boot up, then pasting in a line of code. The compute server gets configured, starts up, and we are able to confirm that the H100 is available. We then type "conda install -y pytorch" to install pytorch, and use Claude3 to run a demo involving the GPU and train a toy model.