diff --git a/ldm/data/simple.py b/ldm/data/simple.py
index 4d200b28..e6b57e8d 100644
--- a/ldm/data/simple.py
+++ b/ldm/data/simple.py
@@ -63,10 +63,11 @@ def hf_dataset(
     split='train',
     image_key='image',
     caption_key='txt',
+    use_auth_token=False,
     ):
     """Make huggingface dataset with appropriate list of transforms applied
     """
-    ds = load_dataset(name, split=split)
+    ds = load_dataset(name, split=split, use_auth_token=use_auth_token)
     image_transforms = [instantiate_from_config(tt) for tt in image_transforms]
     image_transforms.extend([transforms.ToTensor(),
                                 transforms.Lambda(lambda x: rearrange(x * 2. - 1., 'c h w -> h w c'))])
@@ -112,4 +113,4 @@ def __getitem__(self, index):
     def _load_caption_file(self, filename):
         with open(filename, 'rt') as f:
             captions = f.readlines()
-        return [x.strip('\n') for x in captions]
\ No newline at end of file
+        return [x.strip('\n') for x in captions]
diff --git a/main.py b/main.py
index b21a775f..bbd785f1 100644
--- a/main.py
+++ b/main.py
@@ -855,7 +855,7 @@ def check_frequency(self, check_idx):
         # configure learning rate
         bs, base_lr = config.data.params.batch_size, config.model.base_learning_rate
         if not cpu:
-            ngpu = len(lightning_config.trainer.gpus.strip(",").split(','))
+            ngpu = len(str(lightning_config.trainer.gpus).strip(",").split(','))
         else:
             ngpu = 1
         if 'accumulate_grad_batches' in lightning_config.trainer: