Update README.md

README.md

@@ -2,6 +2,8 @@
 
 Dataset created using [this script](https://github.com/Birch-san/sdxl-diffusion-decoder/blob/main/script/make_sdxl_latent_dataset.py).
 
+VAE encoder used NATTEN attention, kernel size 17.
+
 Didn't bother saving mean & logvar, because variance is low enough it's not worth the doubling of filesize to retain.  
 Sampled from diagonal gaussian distribution, saved the resulting latents.  
 Also kept the original image.
@@ -15,8 +17,8 @@ Sample = TypedDict('Sample', {
   '__key__': str,
   '__url__': str,
   'cls.txt': bytes, # UTF-8 encoded class id from 0 to 9 inclusive
-  'img.png': bytes, # PIL image, serialized. 256*256px
-  'latent.pth': bytes, # FloatTensor, serialized. 32*32 latents
+  'img.png': bytes, # PIL image, serialized. 1024*1024px
+  'latent.pth': bytes, # FloatTensor, serialized. 128*128 latents
 })
 
 it: Iterator[Sample] = WebDataset('train/{00000..00004}.tar')