diff --git a/tutorials/notebooks/imx500_notebooks/keras/example_keras_effdet_lite0_for_imx500.ipynb b/tutorials/notebooks/imx500_notebooks/keras/example_keras_effdet_lite0_for_imx500.ipynb
index a1b5f0369..df0a1c6c0 100644
--- a/tutorials/notebooks/imx500_notebooks/keras/example_keras_effdet_lite0_for_imx500.ipynb
+++ b/tutorials/notebooks/imx500_notebooks/keras/example_keras_effdet_lite0_for_imx500.ipynb
@@ -7,7 +7,7 @@
     "\n",
     "[Run this tutorial in Google Colab](https://colab.research.google.com/github/sony/model_optimization/blob/main/tutorials/notebooks/imx500_notebooks/keras/example_keras_effdet_lite0_for_imx500.ipynb)\n",
     "\n",
-    "## Overview\n",
+    "## Overview \n",
     "\n",
     "In this notebook, we'll demonstrate the post-training quantization using MCT for a pre-trained object detection model in Keras. In addition, we'll integrate a post-processing custom layer from [sony-custom-layers](https://github.com/sony/custom_layers) into the model. This custom layer is supported by the imx500 target platform capabilities.\n",
     "\n",
@@ -351,6 +351,8 @@
    "execution_count": null,
    "outputs": [],
    "source": [
+    "import model_compression_toolkit as mct\n",
+    "\n",
     "loader, _ = get_coco_dataloader(split='val', config=config)\n",
     "\n",
     "\n",