diff --git a/ch03/02_bonus_efficient-multihead-attention/mha-implementations.ipynb b/ch03/02_bonus_efficient-multihead-attention/mha-implementations.ipynb
index 7cc1058..53795ca 100644
--- a/ch03/02_bonus_efficient-multihead-attention/mha-implementations.ipynb
+++ b/ch03/02_bonus_efficient-multihead-attention/mha-implementations.ipynb
@@ -259,11 +259,11 @@
     "        qkv = qkv.permute(2, 0, 3, 1, 4)\n",
     "\n",
     "        # (3, b, num_heads, num_tokens, head_dim) -> 3 times (b, num_heads, num_tokens, head_dim)\n",
-    "        q, k, v = qkv.unbind(0)\n",
+    "        queries, keys, values = qkv.unbind(0)\n",
     "\n",
     "        use_dropout = 0. if not self.training else self.dropout\n",
-    "        context_vec = torch.nn.functional.scaled_dot_product_attention(q, k, v, \n",
-    "            attn_mask=None, dropout_p=use_dropout, is_causal=True)\n",
+    "        context_vec = nn.functional.scaled_dot_product_attention(\n",
+    "            queries, keys, values, attn_mask=None, dropout_p=use_dropout, is_causal=True)\n",
     "\n",
     "        # Combine heads, where self.d_out = self.num_heads * self.head_dim\n",
     "        context_vec = context_vec.transpose(1, 2).contiguous().view(batch_size, num_tokens, self.d_out)\n",
@@ -396,7 +396,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.10.6"
+   "version": "3.10.12"
   }
  },
  "nbformat": 4,