how its really into the performance and see for at an SV hm so here are the numbers you can see that it's not only working in the regime where you have 4,000 label examples but it works all the way well even when you have 250 labels mixed masses able to get all the way down to 10% error rate on CFR which is a which is very impressive so 250 images for class this means when two to three images of labels just means 25 images per class and you stood ability gets a classifier that gets around 90% accuracy so that's it for mixed match an