diff --git a/ch03/02_bonus_efficient-multihead-attention/mha-implementations.ipynb b/ch03/02_bonus_efficient-multihead-attention/mha-implementations.ipynb
index 240e79b..e6236d4 100644
--- a/ch03/02_bonus_efficient-multihead-attention/mha-implementations.ipynb
+++ b/ch03/02_bonus_efficient-multihead-attention/mha-implementations.ipynb
@@ -58,7 +58,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "PyTorch version: 2.6.0+cu124\n"
+      "PyTorch version: 2.8.0\n"
      ]
     }
    ],
@@ -89,7 +89,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": null,
+   "execution_count": 2,
    "id": "1db27f43-86f4-478f-89df-fbc2182a129b",
    "metadata": {
     "id": "1db27f43-86f4-478f-89df-fbc2182a129b"
@@ -114,7 +114,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 3,
    "id": "297c93ed-aec0-4896-bb89-42c4b294d3d1",
    "metadata": {
     "colab": {
@@ -205,7 +205,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 4,
    "id": "4ee6a61b-d25c-4a0c-8a59-f285544e3710",
    "metadata": {
     "colab": {
@@ -326,7 +326,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "9a6bd0a2-f27c-4602-afa0-c96cd295c1a6",
    "metadata": {
     "colab": {
@@ -434,7 +434,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "id": "92481814-068d-439b-a65c-b1310ebbe0aa",
    "metadata": {
     "colab": {
@@ -466,7 +466,6 @@
     "        self.num_heads = num_heads\n",
     "        self.head_dim = d_out // num_heads\n",
     "\n",
-    "        # Initialize parameters for Q, K, V\n",
     "        self.W_query = nn.Parameter(torch.randn(d_out, d_in))\n",
     "        self.W_key = nn.Parameter(torch.randn(d_out, d_in))\n",
     "        self.W_value = nn.Parameter(torch.randn(d_out, d_in))\n",
@@ -483,8 +482,6 @@
     "        self.out_proj = nn.Linear(d_out, d_out)\n",
     "        self.dropout = nn.Dropout(dropout)\n",
     "        self.register_buffer(\"mask\", torch.triu(torch.ones(context_length, context_length), diagonal=1))\n",
-    "\n",
-    "        # Initialize parameters\n",
     "        self.reset_parameters()\n",
     "\n",
     "\n",