Use batch size consistently

I found it a bit confusing that the output is described in one place as (batch_size, num_features) and in another place as (1, num_features). I suggest sticking with one method and think that (batch_size,...) gives more information

README.md

@@ -74,10 +74,10 @@ output = model(transforms(img).unsqueeze(0))  # output is (batch_size, num_featu
 # or equivalently (without needing to set num_classes=0)
 
 output = model.forward_features(transforms(img).unsqueeze(0))
-# output is unpooled, a (1, 257, 1408) shaped tensor
+# output is unpooled, a (batch_size, 257, 1408) shaped tensor
 
 output = model.forward_head(output, pre_logits=True)
-# output is a (1, num_features) shaped tensor
+# output is a (batch_size, num_features) shaped tensor
 ```
 
 ## Model Comparison