How much time do you lose setting up a rented GPU before you can actually start working?
Whenever I rent a cloud GPU for an experiment or a Kaggle competition, the first 30–60 minutes go on setup: finding an image with the right CUDA and PyTorch versions, SSH keys, installing packages, copying my Kaggle and Hugging Face tokens over, and then remembering to shut it down so it doesn't burn credit.
I'm curious how others deal with this:
What do you use for GPUs today (Colab, Kaggle notebooks, a cloud provider, your own card)?
Which part of the setup annoys you most, or have you got it down to a routine?
If something gave you Jupyter with PyTorch and your Kaggle/HF tokens ready in about a minute, would that matter to you, or is raw price the only thing that counts?
Context: I've been building a small tool around this for my own use and I'm trying to work out whether it's worth turning into something other people could use. Genuinely interested in how you all handle it.