diff --git a/12_custom_models_and_training_with_tensorflow.ipynb b/12_custom_models_and_training_with_tensorflow.ipynb
index c5aa1a8..8f17e3b 100644
--- a/12_custom_models_and_training_with_tensorflow.ipynb
+++ b/12_custom_models_and_training_with_tensorflow.ipynb
@@ -1900,7 +1900,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 147,
+   "execution_count": 2,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -1922,7 +1922,36 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 148,
+   "execution_count": 3,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class GaussianNoiseModel(keras.Model):\n",
+    "    def __init__(self, units, activation, **kwargs):\n",
+    "        super(GaussianNoiseModel, self).__init__(**kwargs)\n",
+    "        self.noise = AddGaussianNoise(stddev=1.0)\n",
+    "        self.hidden = keras.layers.Dense(units, activation=activation)\n",
+    "        self.out = keras.layers.Dense(1)\n",
+    "    \n",
+    "    def call(self, inputs):\n",
+    "        noise = self.noise(inputs)\n",
+    "        hidden = self.hidden(noise)\n",
+    "        out = self.out(hidden)\n",
+    "        return out"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "model = GaussianNoiseModel(units=30, activation='selu')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -3883,7 +3912,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.7.10"
+   "version": "3.8.10"
   }
  },
  "nbformat": 4,