diff --git a/ch02/01_main-chapter-code/ch02.ipynb b/ch02/01_main-chapter-code/ch02.ipynb
index ba0d757..5d24c15 100644
--- a/ch02/01_main-chapter-code/ch02.ipynb
+++ b/ch02/01_main-chapter-code/ch02.ipynb
@@ -26,7 +26,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "torch version: 2.0.1\n",
+      "torch version: 2.1.0\n",
       "tiktoken version: 0.5.1\n"
      ]
     }
@@ -559,7 +559,7 @@
       "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
       "\u001b[0;31mKeyError\u001b[0m                                  Traceback (most recent call last)",
       "Cell \u001b[0;32mIn[16], line 5\u001b[0m\n\u001b[1;32m      1\u001b[0m tokenizer \u001b[38;5;241m=\u001b[39m SimpleTokenizerV1(vocab)\n\u001b[1;32m      3\u001b[0m text \u001b[38;5;241m=\u001b[39m \u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mHello, do you like tea. Is this-- a test?\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[0;32m----> 5\u001b[0m \u001b[43mtokenizer\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mencode\u001b[49m\u001b[43m(\u001b[49m\u001b[43mtext\u001b[49m\u001b[43m)\u001b[49m\n",
-      "Cell \u001b[0;32mIn[12], line 9\u001b[0m, in \u001b[0;36mSimpleTokenizerV1.encode\u001b[0;34m(self, text)\u001b[0m\n\u001b[1;32m      7\u001b[0m preprocessed \u001b[38;5;241m=\u001b[39m re\u001b[38;5;241m.\u001b[39msplit(\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m([,.?_!\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m()\u001b[39m\u001b[38;5;130;01m\\'\u001b[39;00m\u001b[38;5;124m]|--|\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124ms)\u001b[39m\u001b[38;5;124m'\u001b[39m, text)\n\u001b[1;32m      8\u001b[0m preprocessed \u001b[38;5;241m=\u001b[39m [item\u001b[38;5;241m.\u001b[39mstrip() \u001b[38;5;28;01mfor\u001b[39;00m item \u001b[38;5;129;01min\u001b[39;00m preprocessed \u001b[38;5;28;01mif\u001b[39;00m item\u001b[38;5;241m.\u001b[39mstrip()]\n\u001b[0;32m----> 9\u001b[0m ids \u001b[38;5;241m=\u001b[39m \u001b[43m[\u001b[49m\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstr_to_int\u001b[49m\u001b[43m[\u001b[49m\u001b[43ms\u001b[49m\u001b[43m]\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;28;43;01mfor\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43ms\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;129;43;01min\u001b[39;49;00m\u001b[43m \u001b[49m\u001b[43mpreprocessed\u001b[49m\u001b[43m]\u001b[49m\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ids\n",
+      "Cell \u001b[0;32mIn[12], line 9\u001b[0m, in \u001b[0;36mSimpleTokenizerV1.encode\u001b[0;34m(self, text)\u001b[0m\n\u001b[1;32m      7\u001b[0m preprocessed \u001b[38;5;241m=\u001b[39m re\u001b[38;5;241m.\u001b[39msplit(\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m([,.?_!\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m()\u001b[39m\u001b[38;5;130;01m\\'\u001b[39;00m\u001b[38;5;124m]|--|\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124ms)\u001b[39m\u001b[38;5;124m'\u001b[39m, text)\n\u001b[1;32m      8\u001b[0m preprocessed \u001b[38;5;241m=\u001b[39m [item\u001b[38;5;241m.\u001b[39mstrip() \u001b[38;5;28;01mfor\u001b[39;00m item \u001b[38;5;129;01min\u001b[39;00m preprocessed \u001b[38;5;28;01mif\u001b[39;00m item\u001b[38;5;241m.\u001b[39mstrip()]\n\u001b[0;32m----> 9\u001b[0m ids \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mstr_to_int[s] \u001b[38;5;28;01mfor\u001b[39;00m s \u001b[38;5;129;01min\u001b[39;00m preprocessed]\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ids\n",
       "Cell \u001b[0;32mIn[12], line 9\u001b[0m, in \u001b[0;36m<listcomp>\u001b[0;34m(.0)\u001b[0m\n\u001b[1;32m      7\u001b[0m preprocessed \u001b[38;5;241m=\u001b[39m re\u001b[38;5;241m.\u001b[39msplit(\u001b[38;5;124mr\u001b[39m\u001b[38;5;124m'\u001b[39m\u001b[38;5;124m([,.?_!\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124m()\u001b[39m\u001b[38;5;130;01m\\'\u001b[39;00m\u001b[38;5;124m]|--|\u001b[39m\u001b[38;5;124m\\\u001b[39m\u001b[38;5;124ms)\u001b[39m\u001b[38;5;124m'\u001b[39m, text)\n\u001b[1;32m      8\u001b[0m preprocessed \u001b[38;5;241m=\u001b[39m [item\u001b[38;5;241m.\u001b[39mstrip() \u001b[38;5;28;01mfor\u001b[39;00m item \u001b[38;5;129;01min\u001b[39;00m preprocessed \u001b[38;5;28;01mif\u001b[39;00m item\u001b[38;5;241m.\u001b[39mstrip()]\n\u001b[0;32m----> 9\u001b[0m ids \u001b[38;5;241m=\u001b[39m [\u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mstr_to_int\u001b[49m\u001b[43m[\u001b[49m\u001b[43ms\u001b[49m\u001b[43m]\u001b[49m \u001b[38;5;28;01mfor\u001b[39;00m s \u001b[38;5;129;01min\u001b[39;00m preprocessed]\n\u001b[1;32m     10\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m ids\n",
       "\u001b[0;31mKeyError\u001b[0m: 'Hello'"
      ]
@@ -1102,7 +1102,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "PyTorch version: 2.0.1\n"
+      "PyTorch version: 2.1.0\n"
      ]
     }
    ],
@@ -1159,7 +1159,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "def create_dataloader_v1(txt, batch_size=4, max_length=256, stride=128, shuffle=True):\n",
+    "def create_dataloader_v1(txt, batch_size=4, max_length=256, stride=128, shuffle=True, drop_last=True):\n",
+    "\n",
     "    # Initialize the tokenizer\n",
     "    tokenizer = tiktoken.get_encoding(\"gpt2\")\n",
     "\n",
@@ -1167,7 +1168,8 @@
     "    dataset = GPTDatasetV1(txt, tokenizer, max_length, stride)\n",
     "\n",
     "    # Create dataloader\n",
-    "    dataloader = DataLoader(dataset, batch_size=batch_size, shuffle=shuffle)\n",
+    "    dataloader = DataLoader(\n",
+    "        dataset, batch_size=batch_size, shuffle=shuffle, drop_last=drop_last)\n",
     "\n",
     "    return dataloader"
    ]
@@ -1638,7 +1640,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,
diff --git a/ch02/01_main-chapter-code/dataloader.ipynb b/ch02/01_main-chapter-code/dataloader.ipynb
index b6ce60c..519ca43 100644
--- a/ch02/01_main-chapter-code/dataloader.ipynb
+++ b/ch02/01_main-chapter-code/dataloader.ipynb
@@ -78,7 +78,8 @@
     "        return self.input_ids[idx], self.target_ids[idx]\n",
     "\n",
     "\n",
-    "def create_dataloader_v1(txt, batch_size=4, max_length=256, stride=128, shuffle=True):\n",
+    "def create_dataloader_v1(txt, batch_size=4, max_length=256, \n",
+    "                         stride=128, shuffle=True, drop_last=True):\n",
     "    # Initialize the tokenizer\n",
     "    tokenizer = tiktoken.get_encoding(\"gpt2\")\n",
     "\n",
@@ -86,12 +87,12 @@
     "    dataset = GPTDatasetV1(txt, tokenizer, max_length, stride)\n",
     "\n",
     "    # Create dataloader\n",
-    "    dataloader = DataLoader(dataset, batch_size=batch_size, shuffle=shuffle)\n",
+    "    dataloader = DataLoader(\n",
+    "        dataset, batch_size=batch_size, shuffle=shuffle, drop_last=drop_last)\n",
     "\n",
     "    return dataloader\n",
     "\n",
     "\n",
-    "\n",
     "with open(\"the-verdict.txt\", \"r\", encoding=\"utf-8\") as f:\n",
     "    raw_text = f.read()\n",
     "\n",
@@ -163,7 +164,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.11.4"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,
diff --git a/ch04/01_main-chapter-code/gpt.py b/ch04/01_main-chapter-code/gpt.py
index baa58b2..b3e1335 100644
--- a/ch04/01_main-chapter-code/gpt.py
+++ b/ch04/01_main-chapter-code/gpt.py
@@ -35,7 +35,8 @@ class GPTDatasetV1(Dataset):
         return self.input_ids[idx], self.target_ids[idx]
 
 
-def create_dataloader(txt, batch_size=4, max_length=256, stride=128, shuffle=True):
+def create_dataloader_v1(txt, batch_size=4, max_length=256, 
+                         stride=128, shuffle=True, drop_last=True):
     # Initialize the tokenizer
     tokenizer = tiktoken.get_encoding("gpt2")
 
@@ -43,7 +44,8 @@ def create_dataloader(txt, batch_size=4, max_length=256, stride=128, shuffle=Tru
     dataset = GPTDatasetV1(txt, tokenizer, max_length, stride)
 
     # Create dataloader
-    dataloader = DataLoader(dataset, batch_size=batch_size, shuffle=shuffle)
+    dataloader = DataLoader(
+        dataset, batch_size=batch_size, shuffle=shuffle, drop_last=drop_last)
 
     return dataloader
 
diff --git a/ch04/01_main-chapter-code/previous_chapters.py b/ch04/01_main-chapter-code/previous_chapters.py
index b328743..28426cd 100644
--- a/ch04/01_main-chapter-code/previous_chapters.py
+++ b/ch04/01_main-chapter-code/previous_chapters.py
@@ -27,7 +27,8 @@ class GPTDatasetV1(Dataset):
         return self.input_ids[idx], self.target_ids[idx]
 
 
-def create_dataloader_v1(txt, batch_size=4, max_length=256, stride=128, shuffle=True):
+def create_dataloader_v1(txt, batch_size=4, max_length=256, 
+                         stride=128, shuffle=True, drop_last=True):
     # Initialize the tokenizer
     tokenizer = tiktoken.get_encoding("gpt2")
 
@@ -35,7 +36,8 @@ def create_dataloader_v1(txt, batch_size=4, max_length=256, stride=128, shuffle=
     dataset = GPTDatasetV1(txt, tokenizer, max_length, stride)
 
     # Create dataloader
-    dataloader = DataLoader(dataset, batch_size=batch_size, shuffle=shuffle)
+    dataloader = DataLoader(
+        dataset, batch_size=batch_size, shuffle=shuffle, drop_last=drop_last)
 
     return dataloader