diff --git a/pretrain/dataset.py b/pretrain/dataset.py
index de19704..fbc50bf 100644
--- a/pretrain/dataset.py
+++ b/pretrain/dataset.py
@@ -12,17 +12,17 @@
 from pprint import pprint
 
 import os
-from dotenv import load_dotenv  
+from dotenv import load_dotenv
 load_dotenv()
 
 class SubsetLoader(IterableDataset):
     """Base class for data-specific subset loader classes."""
-    
+
     name: str = None  # Dataset name
     rows_base_url: str = "https://datasets-server.huggingface.co/rows"
     size_base_url: str = "https://datasets-server.huggingface.co/size"
     max_pages: int = None
-    
+
     def __init__(
         self,
         batch_size=None,
@@ -78,9 +78,9 @@ def __init__(
                 self._initialize_pages()
                 fetch_attempt += 1
 
-                # Exit if the buffer has at least one batch            
+                # Exit if the buffer has at least one batch
                 if len(self.buffer) >= self.sequence_length:
-                    break  
+                    break
 
                 bt.logging.warning(
                     f"All fetched pages seem to be empty or have an extremely low token count. "
@@ -139,14 +139,14 @@ def _fetch_data_for_page(self, page):
             })
         else:
             self.params["offset"] = page
-            
+
         self.params["length"] = self.num_rows_per_page
-        
+
         attempt = 0
         while attempt < self.retry_limit:
             try:
                 response = requests.get(
-                    self.rows_base_url, 
+                    self.rows_base_url,
                     params=self.params,
                     headers=self._get_request_headers()
                 )
@@ -183,9 +183,9 @@ def get_page_names(self):
         """Get page names in consistent format"""
         if not hasattr(self, 'pages'):
             return []
-            
+
         if isinstance(self.pages[0], tuple):
-            return [f"{cfg_name}_{num_rows}_{split}" 
+            return [f"{cfg_name}_{num_rows}_{split}"
                    for cfg_name, num_rows, split in self.pages]
         return self.pages
 
@@ -257,15 +257,15 @@ def __init__(self, **kwargs):
             aws_secret_access_key=os.environ["AWS_SECRET_ACCESS_KEY"])
 
         self.s3_sess = session.client("s3")
-        
+
         super().__init__(requires_auth=True, **kwargs)
-        
+
 
     def _download_row_content(self, blob_id, src_encoding):
         """Download the row content from S3.
         """
-        
-        s3_url = f"s3://softwareheritage/content/{blob_id}"
+
+        s3_url = f"https://softwareheritage.s3.amazonaws.com/content/{blob_id}"
 
         with smart_open.open(s3_url, "rb", compression=".gz", transport_params={"client": self.s3_sess}) as fin:
             content = fin.read().decode(src_encoding)
@@ -277,7 +277,7 @@ def _get_content_from_row(self, row):
 
         content = self._download_row_content(row['row']['blob_id'], row['row']['src_encoding'])
         return content
-        
+
 
 class SubsetFalconLoader(SubsetLoader):
     max_pages: int = 968000015
@@ -286,14 +286,14 @@ class SubsetFalconLoader(SubsetLoader):
 
 class SubsetFineWebEdu2Loader(SubsetLoader):
     name: str = "HuggingFaceFW/fineweb-edu-score-2"
-    
+
     def fetch_dataset_configs(self) -> typing.Dict[str, typing.Dict]:
         """
         Fetch dataset configs and their metadata.
         Returns a dictionary with config names as keys and metadata as values.
         """
         params = dict(dataset=self.name)
-        
+
         attempt = 0
         while attempt < self.retry_limit:
             try:
@@ -385,7 +385,7 @@ def get_random_pages(self, num_pages, initial_offset):
             split = self.configs_data[config_name]["split"]
             pages.append((config_name, selected_page_start, split))
         return pages
-    
+
     def fetch_data_to_rows(self, num_pages):
         """Fetch data and return raw text rows instead of adding to buffer."""
         downloaded_pages = set()