I think the other comments are spot on. It depends on your data. How many time series are you needing to predict for? How 'multivariate' is your data meaning do you have a ton of variables or only a few?

Don't know about modeltime but both darts and sktime are fine. But if you have a lot of good quality variables then it's worth trying boosted trees and 'featurizing' time. If you just have holidays then probably best to stick with time series approaches.

If you also have multiple time series which are related such as products that belong to different categories or something like that -trees may also be worth taking a look at if you pass those categories as variables. Alternatively you could look at hierarchical methods like what is in Nixtla's portfolio of packages.

But definitely give us some more info!