diff --git a/zoobot/pytorch/datasets/webdatamodule.py b/zoobot/pytorch/datasets/webdatamodule.py
index 075f4201..2968bd2b 100644
--- a/zoobot/pytorch/datasets/webdatamodule.py
+++ b/zoobot/pytorch/datasets/webdatamodule.py
@@ -1,5 +1,5 @@
 import os
-import types
+from typing import Callable
 import logging
 import torch.utils.data
 import numpy as np
@@ -27,7 +27,8 @@ def __init__(
             color=False,
             crop_scale_bounds=(0.7, 0.8),
             crop_ratio_bounds=(0.9, 1.1),
-            resize_after_crop=224
+            resize_after_crop=224,
+            transform: Callable=None
             ):
         super().__init__()
 
@@ -60,6 +61,8 @@ def __init__(
         self.crop_scale_bounds = crop_scale_bounds
         self.crop_ratio_bounds = crop_ratio_bounds
 
+        self.transform = transform
+
         for url_name in ['train', 'val', 'test', 'predict']:
             urls = getattr(self, f'{url_name}_urls')
             if urls is not None:
@@ -98,7 +101,12 @@ def make_loader(self, urls, mode="train"):
             assert mode in ['val', 'test', 'predict'], mode
             shuffle = 0
 
-        transform_image = self.make_image_transform(mode=mode)
+        if self.transform is None:
+            logging.info('Using default transform')
+            transform_image = self.make_image_transform(mode=mode)
+        else:
+            logging.info('Ignoring hparams and using directly-passed transform')
+            transform_image = self.transform
 
         transform_label = dict_to_label_cols_factory(self.label_cols)
 
@@ -109,7 +117,8 @@ def make_loader(self, urls, mode="train"):
         if shuffle > 0:
             dataset = dataset.shuffle(shuffle)
 
-        dataset = dataset.decode("rgb")
+        # dataset = dataset.decode("rgb")  # np.array, for albumentations
+        dataset = dataset.decode("pilrgb")  # PIL Image, for torchvision
     
         if mode == 'predict':
             if self.label_cols != ['id_str']:
diff --git a/zoobot/pytorch/training/train_with_pytorch_lightning.py b/zoobot/pytorch/training/train_with_pytorch_lightning.py
index ce3e0529..da734dec 100644
--- a/zoobot/pytorch/training/train_with_pytorch_lightning.py
+++ b/zoobot/pytorch/training/train_with_pytorch_lightning.py
@@ -235,6 +235,23 @@ def train_default_zoobot_from_scratch(
         )
     else:
         # this branch will use WebDataModule to load premade webdatasets
+
+        # temporary: use SSL-like transform
+        from foundation.models import transforms
+        # from omegaconf import DictConfig
+        # cfg = DictConfig({
+        #     'aug': {
+        #         'global_transform_0': {
+        #             'interpolation': 'bilinear',
+        #             'random_affine': {}  # etc
+        #         }
+                
+        #     }
+        # })
+        cfg = transforms.default_view_config()
+        cfg.output_size = resize_after_crop
+        transform = transforms.GalaxyViewTransform(cfg)
+
         datamodule = webdatamodule.WebDataModule(
             train_urls=train_urls,
             val_urls=val_urls,
@@ -246,10 +263,11 @@ def train_default_zoobot_from_scratch(
             prefetch_factor=prefetch_factor,
             cache_dir=cache_dir,
             # augmentation args
-            color=color,
-            crop_scale_bounds=crop_scale_bounds,
-            crop_ratio_bounds=crop_ratio_bounds,
-            resize_after_crop=resize_after_crop
+            transform=transform,
+            # color=color,
+            # crop_scale_bounds=crop_scale_bounds,
+            # crop_ratio_bounds=crop_ratio_bounds,
+            # resize_after_crop=resize_after_crop
         )
 
     datamodule.setup(stage='fit')