diff --git a/notebooks/keras_fashion_mnist.ipynb b/notebooks/keras_fashion_mnist.ipynb
index a1e2b36..6e751ec 100644
--- a/notebooks/keras_fashion_mnist.ipynb
+++ b/notebooks/keras_fashion_mnist.ipynb
@@ -16,7 +16,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "modelscan, version 0.5.0\n"
+      "modelscan, version 0.5.1\n"
      ]
     }
    ],
@@ -48,6 +48,37 @@
     "from utils.tensorflow_fashion_mnist_model import train_model, get_predictions"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Optional Settings File for ModelScan\n",
+    "\n",
+    "ModelScan scan settings can be configured using a settings file. \n",
+    "\n",
+    "- To create a configurable settings file use: `modelscan create-settings-file` (creates a `modelscan-settings.toml` file in current directory). \n",
+    "\n",
+    "- The location and name of a settings file can also be specified with `modelscan create-settings-file -l ../path-to/settings-file.toml` \n",
+    "\n",
+    "Configurations:\n",
+    "- A settings file would allow enabling/disabling particular scans such as H5LambdaDetectScan, and PickleUnsafeOpScan. \n",
+    "\n",
+    "- A settings file can also be configured to set particular severity level (CRITICAL, HIGH, MEDIUM, or LOW) for unsafe operators. \n",
+    "\n",
+    "- Reporting format for ModelScan results can also be specified in a settings file.\n",
+    "\n",
+    "If you would like to create a configurable settings file, uncomment the code in the next cell and run it. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#!modelscan create-settings-file -l my-modelscan-settings.toml"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -59,7 +90,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -67,35 +98,35 @@
      "output_type": "stream",
      "text": [
       "Epoch 1/10\n",
-      "1875/1875 [==============================] - 2s 1ms/step - loss: 0.4986 - accuracy: 0.8258\n",
+      "1875/1875 [==============================] - 1s 726us/step - loss: 0.4961 - accuracy: 0.8248\n",
       "Epoch 2/10\n",
-      "1875/1875 [==============================] - 2s 800us/step - loss: 0.3741 - accuracy: 0.8649\n",
+      "1875/1875 [==============================] - 1s 689us/step - loss: 0.3736 - accuracy: 0.8641\n",
       "Epoch 3/10\n",
-      "1875/1875 [==============================] - 1s 772us/step - loss: 0.3391 - accuracy: 0.8766\n",
+      "1875/1875 [==============================] - 1s 718us/step - loss: 0.3351 - accuracy: 0.8782\n",
       "Epoch 4/10\n",
-      "1875/1875 [==============================] - 1s 755us/step - loss: 0.3125 - accuracy: 0.8852\n",
+      "1875/1875 [==============================] - 1s 716us/step - loss: 0.3147 - accuracy: 0.8829\n",
       "Epoch 5/10\n",
-      "1875/1875 [==============================] - 2s 965us/step - loss: 0.2955 - accuracy: 0.8908\n",
+      "1875/1875 [==============================] - 1s 713us/step - loss: 0.2960 - accuracy: 0.8908\n",
       "Epoch 6/10\n",
-      "1875/1875 [==============================] - 2s 905us/step - loss: 0.2808 - accuracy: 0.8963\n",
+      "1875/1875 [==============================] - 1s 715us/step - loss: 0.2797 - accuracy: 0.8963\n",
       "Epoch 7/10\n",
-      "1875/1875 [==============================] - 2s 1ms/step - loss: 0.2696 - accuracy: 0.9004\n",
+      "1875/1875 [==============================] - 1s 715us/step - loss: 0.2672 - accuracy: 0.9008\n",
       "Epoch 8/10\n",
-      "1875/1875 [==============================] - 2s 895us/step - loss: 0.2587 - accuracy: 0.9039\n",
+      "1875/1875 [==============================] - 1s 723us/step - loss: 0.2580 - accuracy: 0.9044\n",
       "Epoch 9/10\n",
-      "1875/1875 [==============================] - 2s 925us/step - loss: 0.2479 - accuracy: 0.9068\n",
+      "1875/1875 [==============================] - 1s 733us/step - loss: 0.2470 - accuracy: 0.9067\n",
       "Epoch 10/10\n",
-      "1875/1875 [==============================] - 2s 893us/step - loss: 0.2406 - accuracy: 0.9112\n",
-      "313/313 [==============================] - 0s 555us/step - loss: 0.3496 - accuracy: 0.8790\n",
+      "1875/1875 [==============================] - 1s 700us/step - loss: 0.2406 - accuracy: 0.9097\n",
+      "313/313 [==============================] - 0s 480us/step - loss: 0.3465 - accuracy: 0.8782\n",
       "\n",
-      "Model trained with test accuracy: 0.8790000081062317\n"
+      "Model trained with test accuracy: 0.8781999945640564\n"
      ]
     },
     {
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/mehrinkiani/mambaforge/envs/py310/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n",
+      "/Users/mehrinkiani/mambaforge/envs/modelscan/lib/python3.10/site-packages/keras/src/engine/training.py:3000: UserWarning: You are saving your model as an HDF5 file via `model.save()`. This file format is considered legacy. We recommend using instead the native Keras format, e.g. `model.save('my_model.keras')`.\n",
       "  saving_api.save_model(\n"
      ]
     }
@@ -119,16 +150,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1/1 [==============================] - 0s 42ms/step\n",
+      "1/1 [==============================] - 0s 34ms/step\n",
       "\n",
-      "The model predicts: ['Ankle boot', 'Pullover', 'Trouser'] with probabilities: [ 98.948  99.926 100.   ]\n",
+      "The model predicts: ['Ankle boot', 'Pullover', 'Trouser'] with probabilities: [ 95.851  99.163 100.   ]\n",
       "\n",
       "The true labels are ['Ankle boot', 'Pullover', 'Trouser']\n"
      ]
@@ -153,15 +184,22 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Scan the Safe Model\n",
+    "# Scan Safe Model\n",
+    "\n",
+    "\n",
+    "The scan results include information on the files scanned, and any issues if found. For the safe model scanned, modelscan finds no model serialization attacks, as expected.\n",
+    "\n",
+    "### ModelScan Settings File\n",
+    "- If you have created a settings file with default name and location (`modelscan-settings.toml`) it would automatically be used when scanning a model. \n",
     "\n",
+    "- If you want to use a  specific name and/or location of settings file, please specify it with `--settings-file` as outlined in the next cell. \n",
     "\n",
-    "The scan results include information on the files scanned, and any issues if found. For the safe model scanned, modelscan finds no model serialization attacks, as expected."
+    "- If you have not created any settings file, ModelScan will scan using default settings.  "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -170,15 +208,19 @@
      "text": [
       "No settings file detected at /Users/mehrinkiani/Documents/modelscan/notebooks/modelscan-settings.toml. Using defaults. \n",
       "\n",
-      "Scanning /Users/mehrinkiani/Documents/modelscan/notebooks/KerasModels/safe_model.h5 using modelscan.scanners.H5LambdaDetectScan model scan\n",
       "\n",
       "\u001b[34m--- Summary ---\u001b[0m\n",
       "\n",
-      "\u001b[32m No issues found! 🎉\u001b[0m\n"
+      "\u001b[32m No issues found! 🎉\u001b[0m\n",
+      "\n",
+      "\u001b[34m--- Skipped --- \u001b[0m\n",
+      "\n",
+      "Total skipped: \u001b[1;36m1\u001b[0m - run with --show-skipped to see the full list.\n"
      ]
     }
    ],
    "source": [
+    "#!modelscan -p ./KerasModels/safe_model.h5 --settings-file my-modelscan-settings.toml\n",
     "!modelscan -p ./KerasModels/safe_model.h5"
    ]
   },
@@ -193,7 +235,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [
     {
@@ -222,7 +264,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -244,7 +286,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -255,9 +297,9 @@
       "aws_secret_access_key=<aws_secret_key>\n",
       "aws_access_key_id=<access_key_id>\n",
       "aws_secret_access_key=<aws_secret_key>\n",
-      "1/1 [==============================] - 0s 35ms/step\n",
+      "1/1 [==============================] - 0s 26ms/step\n",
       "\n",
-      "The model predicts: ['Ankle boot', 'Pullover', 'Trouser'] with probabilities: [ 98.948  99.926 100.   ]\n",
+      "The model predicts: ['Ankle boot', 'Pullover', 'Trouser'] with probabilities: [ 95.851  99.163 100.   ]\n",
       "\n",
       "The true labels are ['Ankle boot', 'Pullover', 'Trouser']\n"
      ]
@@ -284,16 +326,23 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Scan the Unsafe Model\n",
+    "# Scan Unsafe Model\n",
     "\n",
     "The scan results include information on the files scanned, and any issues if found. In this case, a critical severity level issue is found in the unsafe model scanned. \n",
     "\n",
-    "modelscan also outlines the found operator(s) and module(s) deemed unsafe. "
+    "ModelScan also outlines the found operator(s) and module(s) deemed unsafe. \n",
+    "\n",
+    "### ModelScan Settings File\n",
+    "- If you have created a settings file with default name and location (`modelscan-settings.toml`) it would automatically be used when scanning a model. \n",
+    "\n",
+    "- If you want to use a  specific name and/or location of settings file, please specify it with `--settings-file` as outlined in the next cell. \n",
+    "\n",
+    "- If you have not created any settings file, ModelScan will scan using default settings."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -327,6 +376,7 @@
     }
    ],
    "source": [
+    "#!modelscan -p KerasModels/unsafe_model.h5 --settings-file my-modelscan-settings.toml\n",
     "!modelscan -p KerasModels/unsafe_model.h5"
    ]
   },
@@ -349,7 +399,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "metadata": {},
    "outputs": [
     {
@@ -359,7 +409,7 @@
       "No settings file detected at /Users/mehrinkiani/Documents/modelscan/notebooks/modelscan-settings.toml. Using defaults. \n",
       "\n",
       "Scanning /Users/mehrinkiani/Documents/modelscan/notebooks/KerasModels/unsafe_model.h5 using modelscan.scanners.H5LambdaDetectScan model scan\n",
-      "\u001b[1m{\u001b[0m\u001b[32m\"modelscan_version\"\u001b[0m: \u001b[32m\"0.5.0\"\u001b[0m, \u001b[32m\"timestamp\"\u001b[0m: \u001b[32m\"2024-01-25T17:56:36.776966\"\u001b[0m, \n",
+      "\u001b[1m{\u001b[0m\u001b[32m\"modelscan_version\"\u001b[0m: \u001b[32m\"0.5.1\"\u001b[0m, \u001b[32m\"timestamp\"\u001b[0m: \u001b[32m\"2024-02-06T11:00:43.503049\"\u001b[0m, \n",
       "\u001b[32m\"input_path\"\u001b[0m: \n",
       "\u001b[32m\"/Users/mehrinkiani/Documents/modelscan/notebooks/KerasModels/unsafe_model.h5\"\u001b[0m, \n",
       "\u001b[32m\"total_issues\"\u001b[0m: \u001b[1;36m1\u001b[0m, \u001b[32m\"summary\"\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m\"total_issues_by_severity\"\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m\"LOW\"\u001b[0m: \u001b[1;36m0\u001b[0m, \u001b[32m\"MEDIUM\"\u001b[0m: \n",
@@ -389,7 +439,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.10.13 ('py310')",
+   "display_name": "Python 3.10.13 ('modelscan')",
    "language": "python",
    "name": "python3"
   },
@@ -408,7 +458,7 @@
   "orig_nbformat": 4,
   "vscode": {
    "interpreter": {
-    "hash": "bd638e2064d9001d4ca93bc8e56e039dad230900dd235e8a6196f1614960903a"
+    "hash": "4dc76e75b8580a33bdc5a5a988b23a4143f70625528e602e356063408d11834c"
    }
   }
  },
diff --git a/notebooks/pytorch_sentiment_analysis.ipynb b/notebooks/pytorch_sentiment_analysis.ipynb
index 282439b..fb813a0 100644
--- a/notebooks/pytorch_sentiment_analysis.ipynb
+++ b/notebooks/pytorch_sentiment_analysis.ipynb
@@ -7,13 +7,6 @@
     "# Setup "
    ]
   },
-  {
-   "cell_type": "markdown",
-   "metadata": {},
-   "source": [
-    "## Installing ModelScan"
-   ]
-  },
   {
    "cell_type": "code",
    "execution_count": 1,
@@ -23,7 +16,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "modelscan, version 0.5.0\n"
+      "modelscan, version 0.5.1\n"
      ]
     }
    ],
@@ -52,7 +45,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "/Users/mehrinkiani/mambaforge/envs/py310/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
+      "/Users/mehrinkiani/mambaforge/envs/modelscan/lib/python3.10/site-packages/tqdm/auto.py:21: TqdmWarning: IProgress not found. Please update jupyter and ipywidgets. See https://ipywidgets.readthedocs.io/en/stable/user_install.html\n",
       "  from .autonotebook import tqdm as notebook_tqdm\n"
      ]
     },
@@ -72,6 +65,37 @@
     "%env TOKENIZERS_PARALLELISM=false\n"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Optional Settings File for ModelScan\n",
+    "\n",
+    "ModelScan scan settings can be configured using a settings file. \n",
+    "\n",
+    "- To create a configurable settings file use: `modelscan create-settings-file` (creates a `modelscan-settings.toml` file in current directory). \n",
+    "\n",
+    "- The location and name of a settings file can also be specified with `modelscan create-settings-file -l ../path-to/settings-file.toml` \n",
+    "\n",
+    "Configurations:\n",
+    "- A settings file would allow enabling/disabling particular scans such as H5LambdaDetectScan, and PickleUnsafeOpScan. \n",
+    "\n",
+    "- A settings file can also be configured to set particular severity level (CRITICAL, HIGH, MEDIUM, or LOW) for unsafe operators. \n",
+    "\n",
+    "- Reporting format for ModelScan results can also be specified in a settings file.\n",
+    "\n",
+    "If you would like to create a configurable settings file, uncomment the code in the next cell and run it. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#!modelscan create-settings-file -l my-modelscan-settings.toml"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -84,7 +108,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -107,7 +131,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
@@ -128,12 +152,19 @@
    "source": [
     "# Scan Safe Model\n",
     "\n",
-    "The scan results include information on the files scanned, and any issues if found. For the safe model scanned, modelscan finds no model serialization attacks, as expected."
+    "The scan results include information on the files scanned, and any issues if found. For the safe model scanned, modelscan finds no model serialization attacks, as expected.\n",
+    "\n",
+    "### ModelScan Settings File\n",
+    "- If you have created a settings file with default name and location (`modelscan-settings.toml`) it would automatically be used when scanning a model. \n",
+    "\n",
+    "- If you want to use a  specific name and/or location of settings file, please specify it with `--settings-file` as outlined in the next cell. \n",
+    "\n",
+    "- If you have not created any settings file, ModelScan will scan using default settings.  "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -151,13 +182,15 @@
     }
    ],
    "source": [
-    "!modelscan --path PyTorchModels/safe_model.pt"
+    "#!modelscan --path PyTorchModels/safe_model.pt --settings-file my-modelscan-settings.toml\n",
+    "!modelscan --path PyTorchModels/safe_model.pt "
    ]
   },
   {
    "cell_type": "markdown",
    "metadata": {},
    "source": [
+    "\n",
     "# Model Serialization Attack\n",
     "\n",
     "Here malicious code is injected in the safe model to read aws secret keys. The unsafe model is saved at `./PyTorchModels/unsafe_model.pt`"
@@ -165,7 +198,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -197,7 +230,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -222,12 +255,19 @@
     "\n",
     "The scan results include information on the files scanned, and any issues if found. In this case, a critical severity level issue is found in the unsafe model scanned. \n",
     "\n",
-    "modelscan also outlines the found operator(s) and module(s) deemed unsafe. "
+    "ModelScan also outlines the found operator(s) and module(s) deemed unsafe. \n",
+    "\n",
+    "### ModelScan Settings File\n",
+    "- If you have created a settings file with default name and location (`modelscan-settings.toml`) it would automatically be used when scanning a model. \n",
+    "\n",
+    "- If you want to use a  specific name and/or location of settings file, please specify it with `--settings-file` as outlined in the next cell. \n",
+    "\n",
+    "- If you have not created any settings file, ModelScan will scan using default settings."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -261,6 +301,7 @@
     }
    ],
    "source": [
+    "#!modelscan --path PyTorchModels/unsafe_model.pt --settings-file my-modelscan-settings.toml\n",
     "!modelscan --path  ./PyTorchModels/unsafe_model.pt "
    ]
   },
@@ -283,7 +324,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -293,7 +334,7 @@
       "No settings file detected at /Users/mehrinkiani/Documents/modelscan/notebooks/modelscan-settings.toml. Using defaults. \n",
       "\n",
       "Scanning /Users/mehrinkiani/Documents/modelscan/notebooks/PyTorchModels/unsafe_model.pt:unsafe_model/data.pkl using modelscan.scanners.PickleUnsafeOpScan model scan\n",
-      "\u001b[1m{\u001b[0m\u001b[32m\"modelscan_version\"\u001b[0m: \u001b[32m\"0.5.0\"\u001b[0m, \u001b[32m\"timestamp\"\u001b[0m: \u001b[32m\"2024-01-25T17:10:54.306065\"\u001b[0m, \n",
+      "\u001b[1m{\u001b[0m\u001b[32m\"modelscan_version\"\u001b[0m: \u001b[32m\"0.5.1\"\u001b[0m, \u001b[32m\"timestamp\"\u001b[0m: \u001b[32m\"2024-02-06T10:51:35.006602\"\u001b[0m, \n",
       "\u001b[32m\"input_path\"\u001b[0m: \n",
       "\u001b[32m\"/Users/mehrinkiani/Documents/modelscan/notebooks/PyTorchModels/unsafe_model.pt\"\u001b[0m\n",
       ", \u001b[32m\"total_issues\"\u001b[0m: \u001b[1;36m1\u001b[0m, \u001b[32m\"summary\"\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m\"total_issues_by_severity\"\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m\"LOW\"\u001b[0m: \u001b[1;36m0\u001b[0m, \n",
@@ -312,18 +353,11 @@
     "# This will save the scan results in file: pytorch-model-scan-results.json\n",
     "!modelscan --path  ./PyTorchModels/unsafe_model.pt -r json -o pytorch-model-scan-results.json"
    ]
-  },
-  {
-   "cell_type": "code",
-   "execution_count": null,
-   "metadata": {},
-   "outputs": [],
-   "source": []
   }
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.10.13 ('py310')",
+   "display_name": "Python 3.10.13 ('modelscan')",
    "language": "python",
    "name": "python3"
   },
@@ -341,7 +375,7 @@
   },
   "vscode": {
    "interpreter": {
-    "hash": "bd638e2064d9001d4ca93bc8e56e039dad230900dd235e8a6196f1614960903a"
+    "hash": "4dc76e75b8580a33bdc5a5a988b23a4143f70625528e602e356063408d11834c"
    }
   }
  },
diff --git a/notebooks/tensorflow_fashion_mnist.ipynb b/notebooks/tensorflow_fashion_mnist.ipynb
index bdd48e6..a208ca3 100644
--- a/notebooks/tensorflow_fashion_mnist.ipynb
+++ b/notebooks/tensorflow_fashion_mnist.ipynb
@@ -16,7 +16,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "modelscan, version 0.5.0\n"
+      "modelscan, version 0.5.1\n"
      ]
     }
    ],
@@ -49,6 +49,37 @@
     "from utils.tensorflow_codeinjection import MaliciousModule"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Optional Settings File for ModelScan\n",
+    "\n",
+    "ModelScan scan settings can be configured using a settings file. \n",
+    "\n",
+    "- To create a configurable settings file use: `modelscan create-settings-file` (creates a `modelscan-settings.toml` file in current directory). \n",
+    "\n",
+    "- The location and name of a settings file can also be specified with `modelscan create-settings-file -l ../path-to/settings-file.toml` \n",
+    "\n",
+    "Configurations:\n",
+    "- A settings file would allow enabling/disabling particular scans such as H5LambdaDetectScan, and PickleUnsafeOpScan. \n",
+    "\n",
+    "- A settings file can also be configured to set particular severity level (CRITICAL, HIGH, MEDIUM, or LOW) for unsafe operators. \n",
+    "\n",
+    "- Reporting format for ModelScan results can also be specified in a settings file.\n",
+    "\n",
+    "If you would like to create a configurable settings file, uncomment the code in the next cell and run it. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#!modelscan create-settings-file -l my-modelscan-settings.toml"
+   ]
+  },
   {
    "cell_type": "markdown",
    "metadata": {},
@@ -60,7 +91,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "metadata": {},
    "outputs": [
     {
@@ -68,28 +99,28 @@
      "output_type": "stream",
      "text": [
       "Epoch 1/10\n",
-      "1875/1875 [==============================] - 2s 1ms/step - loss: 0.4993 - accuracy: 0.8256\n",
+      "1875/1875 [==============================] - 1s 726us/step - loss: 0.5043 - accuracy: 0.8241\n",
       "Epoch 2/10\n",
-      "1875/1875 [==============================] - 2s 915us/step - loss: 0.3759 - accuracy: 0.8643\n",
+      "1875/1875 [==============================] - 1s 723us/step - loss: 0.3777 - accuracy: 0.8636\n",
       "Epoch 3/10\n",
-      "1875/1875 [==============================] - 2s 925us/step - loss: 0.3380 - accuracy: 0.8761\n",
+      "1875/1875 [==============================] - 1s 697us/step - loss: 0.3380 - accuracy: 0.8758\n",
       "Epoch 4/10\n",
-      "1875/1875 [==============================] - 2s 919us/step - loss: 0.3125 - accuracy: 0.8852\n",
+      "1875/1875 [==============================] - 1s 695us/step - loss: 0.3134 - accuracy: 0.8849\n",
       "Epoch 5/10\n",
-      "1875/1875 [==============================] - 2s 947us/step - loss: 0.2955 - accuracy: 0.8910\n",
+      "1875/1875 [==============================] - 1s 710us/step - loss: 0.2945 - accuracy: 0.8917\n",
       "Epoch 6/10\n",
-      "1875/1875 [==============================] - 2s 839us/step - loss: 0.2819 - accuracy: 0.8951\n",
+      "1875/1875 [==============================] - 1s 718us/step - loss: 0.2813 - accuracy: 0.8960\n",
       "Epoch 7/10\n",
-      "1875/1875 [==============================] - 2s 1ms/step - loss: 0.2708 - accuracy: 0.9000\n",
+      "1875/1875 [==============================] - 1s 704us/step - loss: 0.2675 - accuracy: 0.9005\n",
       "Epoch 8/10\n",
-      "1875/1875 [==============================] - 2s 983us/step - loss: 0.2577 - accuracy: 0.9047\n",
+      "1875/1875 [==============================] - 1s 714us/step - loss: 0.2569 - accuracy: 0.9038\n",
       "Epoch 9/10\n",
-      "1875/1875 [==============================] - 2s 983us/step - loss: 0.2496 - accuracy: 0.9065\n",
+      "1875/1875 [==============================] - 1s 702us/step - loss: 0.2467 - accuracy: 0.9072\n",
       "Epoch 10/10\n",
-      "1875/1875 [==============================] - 2s 818us/step - loss: 0.2387 - accuracy: 0.9109\n",
-      "313/313 [==============================] - 0s 564us/step - loss: 0.4170 - accuracy: 0.8603\n",
+      "1875/1875 [==============================] - 1s 698us/step - loss: 0.2388 - accuracy: 0.9102\n",
+      "313/313 [==============================] - 0s 500us/step - loss: 0.3476 - accuracy: 0.8765\n",
       "\n",
-      "Model trained with test accuracy: 0.8603000044822693\n"
+      "Model trained with test accuracy: 0.8765000104904175\n"
      ]
     }
    ],
@@ -113,16 +144,16 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "1/1 [==============================] - 0s 36ms/step\n",
+      "1/1 [==============================] - 0s 34ms/step\n",
       "\n",
-      "The model predicts: ['Ankle boot', 'Pullover', 'Trouser'] with probabilities: [ 94.768  65.806 100.   ]\n",
+      "The model predicts: ['Ankle boot', 'Pullover', 'Trouser'] with probabilities: [ 94.972  99.955 100.   ]\n",
       "\n",
       "The true labels are ['Ankle boot', 'Pullover', 'Trouser']\n"
      ]
@@ -147,14 +178,21 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Scan the Safe Model \n",
+    "# Scan Safe Model \n",
     "\n",
-    "The scan results include information on the files scanned, and any issues if found. For the safe model scanned, modelscan finds no model serialization attacks, as expected."
+    "The scan results include information on the files scanned, and any issues if found. For the safe model scanned, modelscan finds no model serialization attacks, as expected.\n",
+    "\n",
+    "### ModelScan Settings File\n",
+    "- If you have created a settings file with default name and location (`modelscan-settings.toml`) it would automatically be used when scanning a model. \n",
+    "\n",
+    "- If you want to use a  specific name and/or location of settings file, please specify it with `--settings-file` as outlined in the next cell. \n",
+    "\n",
+    "- If you have not created any settings file, ModelScan will scan using default settings. "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "metadata": {},
    "outputs": [
     {
@@ -178,6 +216,7 @@
     }
    ],
    "source": [
+    "#!modelscan -p ./TensorFlowModels/safe_model --settings-file my-modelscan-settings.toml\n",
     "!modelscan -p ./TensorFlowModels/safe_model"
    ]
   },
@@ -192,7 +231,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "metadata": {},
    "outputs": [],
    "source": [
@@ -217,7 +256,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "metadata": {},
    "outputs": [
     {
@@ -227,9 +266,9 @@
       "File found: /tmp/aws_secret.txt\n",
       "aws_access_key_id=<access_key_id>\n",
       "aws_secret_access_key=<aws_secret_key>\n",
-      "1/1 [==============================] - 0s 48ms/step\n",
+      "1/1 [==============================] - 0s 42ms/step\n",
       "\n",
-      "The model predicts: ['Ankle boot', 'Pullover', 'Trouser'] with probabilities: [ 94.768  65.806 100.   ]\n",
+      "The model predicts: ['Ankle boot', 'Pullover', 'Trouser'] with probabilities: [ 94.972  99.955 100.   ]\n",
       "\n",
       "The true labels are ['Ankle boot', 'Pullover', 'Trouser']\n"
      ]
@@ -256,16 +295,23 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "# Scan the Unsafe Model\n",
+    "# Scan Unsafe Model\n",
     "\n",
     "The scan results include information on the files scanned, and any issues if found. In this case, a critical severity level issue is found in the unsafe model scanned. \n",
     "\n",
-    "modelscan also outlines the found operator(s) and module(s) deemed unsafe. "
+    "ModelScan also outlines the found operator(s) and module(s) deemed unsafe. \n",
+    "\n",
+    "### ModelScan Settings File\n",
+    "- If you have created a settings file with default name and location (`modelscan-settings.toml`) it would automatically be used when scanning a model. \n",
+    "\n",
+    "- If you want to use a  specific name and/or location of settings file, please specify it with `--settings-file` as outlined in the next cell. \n",
+    "\n",
+    "- If you have not created any settings file, ModelScan will scan using default settings."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "metadata": {},
    "outputs": [
     {
@@ -310,6 +356,7 @@
     }
    ],
    "source": [
+    "#!modelscan -p TensorFlowModels/unsafe_model --settings-file my-modelscan-settings.toml\n",
     "!modelscan -p TensorFlowModels/unsafe_model"
    ]
   },
@@ -332,7 +379,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "metadata": {},
    "outputs": [
     {
@@ -344,7 +391,7 @@
       "Scanning /Users/mehrinkiani/Documents/modelscan/notebooks/TensorFlowModels/unsafe_model/fingerprint.pb using modelscan.scanners.SavedModelTensorflowOpScan model scan\n",
       "Scanning /Users/mehrinkiani/Documents/modelscan/notebooks/TensorFlowModels/unsafe_model/keras_metadata.pb using modelscan.scanners.SavedModelLambdaDetectScan model scan\n",
       "Scanning /Users/mehrinkiani/Documents/modelscan/notebooks/TensorFlowModels/unsafe_model/saved_model.pb using modelscan.scanners.SavedModelTensorflowOpScan model scan\n",
-      "\u001b[1m{\u001b[0m\u001b[32m\"modelscan_version\"\u001b[0m: \u001b[32m\"0.5.0\"\u001b[0m, \u001b[32m\"timestamp\"\u001b[0m: \u001b[32m\"2024-01-25T17:56:46.559473\"\u001b[0m, \n",
+      "\u001b[1m{\u001b[0m\u001b[32m\"modelscan_version\"\u001b[0m: \u001b[32m\"0.5.1\"\u001b[0m, \u001b[32m\"timestamp\"\u001b[0m: \u001b[32m\"2024-02-06T10:59:34.374646\"\u001b[0m, \n",
       "\u001b[32m\"input_path\"\u001b[0m: \n",
       "\u001b[32m\"/Users/mehrinkiani/Documents/modelscan/notebooks/TensorFlowModels/unsafe_model\"\u001b[0m\n",
       ", \u001b[32m\"total_issues\"\u001b[0m: \u001b[1;36m2\u001b[0m, \u001b[32m\"summary\"\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m\"total_issues_by_severity\"\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m\"LOW\"\u001b[0m: \u001b[1;36m0\u001b[0m, \n",
@@ -382,7 +429,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.10.13 ('py310')",
+   "display_name": "Python 3.10.13 ('modelscan')",
    "language": "python",
    "name": "python3"
   },
@@ -401,7 +448,7 @@
   "orig_nbformat": 4,
   "vscode": {
    "interpreter": {
-    "hash": "bd638e2064d9001d4ca93bc8e56e039dad230900dd235e8a6196f1614960903a"
+    "hash": "4dc76e75b8580a33bdc5a5a988b23a4143f70625528e602e356063408d11834c"
    }
   }
  },
diff --git a/notebooks/xgboost_diabetes_classification.ipynb b/notebooks/xgboost_diabetes_classification.ipynb
index 4638d19..ccf0bf9 100644
--- a/notebooks/xgboost_diabetes_classification.ipynb
+++ b/notebooks/xgboost_diabetes_classification.ipynb
@@ -18,7 +18,7 @@
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "modelscan, version 0.5.0\n"
+      "modelscan, version 0.5.1\n"
      ]
     }
    ],
@@ -53,19 +53,52 @@
     "from utils.xgboost_diabetes_model import train_model, get_predictions"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "ea9cdc7f",
+   "metadata": {},
+   "source": [
+    "## Optional Settings File for ModelScan\n",
+    "\n",
+    "ModelScan scan settings can be configured using a settings file. \n",
+    "\n",
+    "- To create a configurable settings file use: `modelscan create-settings-file` (creates a `modelscan-settings.toml` file in current directory). \n",
+    "\n",
+    "- The location and name of a settings file can also be specified with `modelscan create-settings-file -l ../path-to/settings-file.toml` \n",
+    "\n",
+    "Configurations:\n",
+    "- A settings file would allow enabling/disabling particular scans such as H5LambdaDetectScan, and PickleUnsafeOpScan. \n",
+    "\n",
+    "- A settings file can also be configured to set particular severity level (CRITICAL, HIGH, MEDIUM, or LOW) for unsafe operators. \n",
+    "\n",
+    "- Reporting format for ModelScan results can also be specified in a settings file.\n",
+    "\n",
+    "If you would like to create a configurable settings file, uncomment the code in the next cell and run it. "
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 4,
+   "id": "9f6e95e5",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "#!modelscan create-settings-file -l my-modelscan-settings.toml"
+   ]
+  },
   {
    "cell_type": "markdown",
    "id": "063dd649",
    "metadata": {},
    "source": [
-    "# Save a XGBoost Model\n",
+    "# Saving Model\n",
     "\n",
     "The model is trained on a diabetes dataset, and predicts whether a person has diabetes or not. The dataset can be found here: [Link to PIMA Indian diabetes dataset](https://www.kaggle.com/datasets/uciml/pima-indians-diabetes-database). The model is saved at ```./XGBoostModels/safe_model.pkl```"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 5,
    "id": "015f415a",
    "metadata": {},
    "outputs": [],
@@ -85,12 +118,12 @@
    "id": "51812303",
    "metadata": {},
    "source": [
-    "# Predict using Safe Model"
+    "# Safe Model Prediction"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 6,
    "id": "8b8d0327",
    "metadata": {},
    "outputs": [
@@ -113,14 +146,21 @@
    "id": "fff6510d",
    "metadata": {},
    "source": [
-    "# Scan the safe model\n",
+    "# Scan Safe Model\n",
+    "\n",
+    "The scan results include information on the files scanned, and any issues if found. For the safe model scanned, modelscan finds no code injections in it, as expected.\n",
+    "\n",
+    "### ModelScan Settings File\n",
+    "- If you have created a settings file with default name and location (`modelscan-settings.toml`) it would automatically be used when scanning a model. \n",
     "\n",
-    "The scan results include information on the files scanned, and any issues if found. For the safe model scanned, modelscan finds no code injections in it, as expected."
+    "- If you want to use a  specific name and/or location of settings file, please specify it with `--settings-file` as outlined in the next cell. \n",
+    "\n",
+    "- If you have not created any settings file, ModelScan will scan using default settings.  "
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 6,
+   "execution_count": 7,
    "id": "ccfeee08",
    "metadata": {},
    "outputs": [
@@ -139,6 +179,7 @@
     }
    ],
    "source": [
+    "#!modelscan -p XGBoostModels/safe_model.pkl --settings-file my-modelscan-settings.toml\n",
     "!modelscan -p XGBoostModels/safe_model.pkl"
    ]
   },
@@ -154,7 +195,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 8,
    "id": "d0e70069",
    "metadata": {},
    "outputs": [],
@@ -167,7 +208,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 9,
    "id": "7bde73cd",
    "metadata": {},
    "outputs": [],
@@ -184,7 +225,7 @@
    "id": "1798152e",
    "metadata": {},
    "source": [
-    "# Predict using Unsafe Model\n",
+    "# Unsafe Model Prediction\n",
     "\n",
     "The malicious code gets executed when the model is loaded. The aws secret keys are displayed. \n",
     "\n",
@@ -193,7 +234,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 10,
    "id": "49d6c62f",
    "metadata": {},
    "outputs": [
@@ -220,16 +261,23 @@
    "id": "72584048",
    "metadata": {},
    "source": [
-    "# Scan the Unsafe Model\n",
+    "# Scan Unsafe Model\n",
     "\n",
     "The scan results include information on the files scanned, and any issues if found. In this case, a critical severity level issue is found in the unsafe model scanned. \n",
     "\n",
-    "modelscan also outlines the found operator(s) and module(s) deemed unsafe. "
+    "ModelScan also outlines the found operator(s) and module(s) deemed unsafe. \n",
+    "\n",
+    "### ModelScan Settings File\n",
+    "- If you have created a settings file with default name and location (`modelscan-settings.toml`) it would automatically be used when scanning a model. \n",
+    "\n",
+    "- If you want to use a  specific name and/or location of settings file, please specify it with `--settings-file` as outlined in the next cell. \n",
+    "\n",
+    "- If you have not created any settings file, ModelScan will scan using default settings."
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 11,
    "id": "9ee3393e",
    "metadata": {},
    "outputs": [
@@ -264,6 +312,7 @@
     }
    ],
    "source": [
+    "#!modelscan -p XGBoostModels/unsafe_model.pkl --settings-file my-modelscan-settings.toml\n",
     "!modelscan -p XGBoostModels/unsafe_model.pkl"
    ]
   },
@@ -288,7 +337,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 11,
+   "execution_count": 12,
    "id": "6df55b3e",
    "metadata": {},
    "outputs": [
@@ -299,7 +348,7 @@
       "No settings file detected at /Users/mehrinkiani/Documents/modelscan/notebooks/modelscan-settings.toml. Using defaults. \n",
       "\n",
       "Scanning /Users/mehrinkiani/Documents/modelscan/notebooks/XGBoostModels/unsafe_model.pkl using modelscan.scanners.PickleUnsafeOpScan model scan\n",
-      "\u001b[1m{\u001b[0m\u001b[32m\"modelscan_version\"\u001b[0m: \u001b[32m\"0.5.0\"\u001b[0m, \u001b[32m\"timestamp\"\u001b[0m: \u001b[32m\"2024-01-25T17:56:00.855056\"\u001b[0m, \n",
+      "\u001b[1m{\u001b[0m\u001b[32m\"modelscan_version\"\u001b[0m: \u001b[32m\"0.5.1\"\u001b[0m, \u001b[32m\"timestamp\"\u001b[0m: \u001b[32m\"2024-02-06T10:56:13.862502\"\u001b[0m, \n",
       "\u001b[32m\"input_path\"\u001b[0m: \n",
       "\u001b[32m\"/Users/mehrinkiani/Documents/modelscan/notebooks/XGBoostModels/unsafe_model.pkl\u001b[0m\n",
       "\u001b[32m\"\u001b[0m, \u001b[32m\"total_issues\"\u001b[0m: \u001b[1;36m1\u001b[0m, \u001b[32m\"summary\"\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m\"total_issues_by_severity\"\u001b[0m: \u001b[1m{\u001b[0m\u001b[32m\"LOW\"\u001b[0m: \u001b[1;36m0\u001b[0m, \n",
@@ -322,7 +371,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3.10.13 ('py310')",
+   "display_name": "Python 3.10.13 ('modelscan')",
    "language": "python",
    "name": "python3"
   },
@@ -340,7 +389,7 @@
   },
   "vscode": {
    "interpreter": {
-    "hash": "bd638e2064d9001d4ca93bc8e56e039dad230900dd235e8a6196f1614960903a"
+    "hash": "4dc76e75b8580a33bdc5a5a988b23a4143f70625528e602e356063408d11834c"
    }
   }
  },