diff --git a/ch02/01_main-chapter-code/ch02.ipynb b/ch02/01_main-chapter-code/ch02.ipynb
index 6c7ee3a..9d1efbf 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: 2.1.0\n",
+      "torch version: 2.0.1\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[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;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;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: 2.1.0\n"
+      "PyTorch version: 2.0.1\n"
      ]
     }
    ],
@@ -1253,28 +1253,28 @@
      "text": [
       "Inputs:\n",
       " tensor([[   40,   367,  2885,  1464],\n",
-      "        [ 3619,   402,   271, 10899],\n",
-      "        [  257,  7026, 15632,   438],\n",
-      "        [  257,   922,  5891,  1576],\n",
+      "        [ 1807,  3619,   402,   271],\n",
+      "        [10899,  2138,   257,  7026],\n",
+      "        [15632,   438,  2016,   257],\n",
+      "        [  922,  5891,  1576,   438],\n",
       "        [  568,   340,   373,   645],\n",
-      "        [ 5975,   284,   502,   284],\n",
-      "        [  326,    11,   287,   262],\n",
-      "        [  286,   465, 13476,    11]])\n",
+      "        [ 1049,  5975,   284,   502],\n",
+      "        [  284,  3285,   326,    11]])\n",
       "\n",
       "Targets:\n",
       " tensor([[  367,  2885,  1464,  1807],\n",
-      "        [  402,   271, 10899,  2138],\n",
-      "        [ 7026, 15632,   438,  2016],\n",
-      "        [  922,  5891,  1576,   438],\n",
+      "        [ 3619,   402,   271, 10899],\n",
+      "        [ 2138,   257,  7026, 15632],\n",
+      "        [  438,  2016,   257,   922],\n",
+      "        [ 5891,  1576,   438,   568],\n",
       "        [  340,   373,   645,  1049],\n",
-      "        [  284,   502,   284,  3285],\n",
-      "        [   11,   287,   262,  6001],\n",
-      "        [  465, 13476,    11,   339]])\n"
+      "        [ 5975,   284,   502,   284],\n",
+      "        [ 3285,   326,    11,   287]])\n"
      ]
     }
    ],
    "source": [
-    "dataloader = create_dataloader_v1(raw_text, batch_size=8, max_length=4, stride=5, shuffle=False)\n",
+    "dataloader = create_dataloader_v1(raw_text, batch_size=8, max_length=4, stride=4, shuffle=False)\n",
     "\n",
     "data_iter = iter(dataloader)\n",
     "inputs, targets = next(data_iter)\n",
@@ -1638,7 +1638,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,
diff --git a/ch02/01_main-chapter-code/dataloader.ipynb b/ch02/01_main-chapter-code/dataloader.ipynb
index 73c58f8..b6ce60c 100644
--- a/ch02/01_main-chapter-code/dataloader.ipynb
+++ b/ch02/01_main-chapter-code/dataloader.ipynb
@@ -28,7 +28,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "torch version: 2.1.0\n",
+      "torch version: 2.0.1\n",
       "tiktoken version: 0.5.1\n"
      ]
     }
@@ -107,7 +107,7 @@
     "pos_embedding_layer = torch.nn.Embedding(block_size, output_dim)\n",
     "\n",
     "max_length = 4\n",
-    "dataloader = create_dataloader_v1(raw_text, batch_size=8, max_length=max_length, stride=5)"
+    "dataloader = create_dataloader_v1(raw_text, batch_size=8, max_length=max_length, stride=max_length)"
    ]
   },
   {
@@ -163,7 +163,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.12"
+   "version": "3.11.4"
   }
  },
  "nbformat": 4,