version one and kept on hacking the architecture the the different type of parameters needed to get get all various patches and like add a lot of details in terms of data augmentations and and see how far we could push the number so and what we ended up doing was like like we actually were able to match or sometimes beat supervised learning on various downstream tasks and I want to go through the details here so you've already looked at this where you grid an image into a bunch of matches and you encode every single pass using a really