From #69:

We could consider adding more informative error messages when running out of memory during Hessian allocation / computation. E.g., if initialising the Hessian runs out of memory, we could raise an error saying something like
"Your model is too big for using FullLaplace. It has X parameters, so the Hessian would be YTB large, while your CPU/GPU only has ZGB memory available. To use FullLaplace on your machine, your model can at most have ~V parameters. Instead, consider using a more memory-efficient Laplace variant, such as W."