LightingModel.save_checkpoint()

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### Description & Motivation

Allow Lightning model to save a checkpoint, that you can load with load_from_checkpoint.

### Pitch

I have encountered this issue several times, as I try to switch to Lightning, it is not simple to take old checkpoints from native pytorch and run them on the new code (for testing/comparison purposes for examples)
I tried to make a model, then load LightningModel.Model with the weights, but then if I want to save it, I need to run a full mock training which isn't handy or practical.

### Alternatives

You could have a simple attach method on the trainer to attach a model without having to use Fit/Test/predict etc... and requiring arguments. Which would be a good alternative.

### Additional context

_No response_

cc @lantiga @borda

Start by reviewing the existing load_from_checkpoint path and how a Lightning model is currently constructed from native PyTorch weights. Define the checkpoint-saving entry point from the issue's requested behavior; done means a model can save a checkpoint that load_from_checkpoint can load without running mock training.

Written by the indexing model from the issue text.