sometimes are really useful for text classification any questions on the strategies those are the three okay so so now we come back to the question of how do we balance the need for having a large model so so when we're dealing with unlabeled data of which we have a really often you have much higher volume you have much more unlabeled data than say labeled data and so you generally would need a very large model to to train on that data so but but you may have a small amount of labeled data so you wanna the question is how to balance