diff --git a/BE2_GAN_and_Diffusion_colab_3.ipynb b/BE2_GAN_and_Diffusion_colab_3.ipynb
index f4a2eee10a00c604cc4d7c86196f1a685893b2c3..6d75e774e424d1373e899b2cb86aab3c1eb3c7a8 100644
--- a/BE2_GAN_and_Diffusion_colab_3.ipynb
+++ b/BE2_GAN_and_Diffusion_colab_3.ipynb
@@ -44738,16 +44738,11 @@
       "source": [
         "<font color='red'>Question</font>  \n",
         "What are the differences between the UNet used for the cGAN generator and the one defined above ?  \n",
-        "Indicate the differences in the architecture by analyzing both models \\_\\_str\\_\\_."
+        "Indicate the differences in the architecture by analyzing both models \\_\\_str\\_\\_.\n",
+        "\n",
+        "The UNet2DModel uses a 1 channel input and the UNet from before a 3 channels input. Furthermore UNet2dModel uses a conditioning on time steps as it is necessary for diffusion. Also it uses SiLu activations instead of LeakyRelu/Relu/tanh. On top of that UNet2dModel uses GroupNorm and the other model uses BatchNorm2d "
       ]
     },
-    {
-      "cell_type": "code",
-      "execution_count": null,
-      "metadata": {},
-      "outputs": [],
-      "source": []
-    },
     {
       "cell_type": "markdown",
       "metadata": {