In my example, it is very helpful if you can adjust a speech model a bit to better match the user's dialect. So you don't train the full model, rather you just adjust the most coarse 5% of parameters in a pre-trained model by a tiny bit. But that can lead to great quality improvements at almost no additional cost.

I'm no expert in ML, one use case is that if you want to refine the already trained model that was trained elsewhere.