diff --git a/12_bedrock/31_continued_pretrainining_titan_shareholder_pdf.ipynb b/12_bedrock/31_continued_pretrainining_titan_shareholder_pdf.ipynb
index 3d9cdac4..654db9de 100644
--- a/12_bedrock/31_continued_pretrainining_titan_shareholder_pdf.ipynb
+++ b/12_bedrock/31_continued_pretrainining_titan_shareholder_pdf.ipynb
@@ -830,8 +830,8 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "#base_model_id = \"amazon.titan-text-express-v1\"\n",
-    "base_model_id = \"amazon.titan-text-lite-v1\""
+    "base_model_id = \"amazon.titan-text-express-v1\"\n",
+    "#base_model_id = \"amazon.titan-text-lite-v1\""
    ]
   },
   {
@@ -882,7 +882,9 @@
   {
    "cell_type": "markdown",
    "id": "3dfa6614-7080-4dbb-af08-cd67ce6a8706",
-   "metadata": {},
+   "metadata": {
+    "tags": []
+   },
    "source": [
     "### Convert PDF to jsonlines format"
    ]
@@ -1370,7 +1372,7 @@
     }
    ],
    "source": [
-    "!aws s3 cp data/train-continual-pretraining.jsonl $s3_location"
+    "!aws s3 cp ./train-continual-pretraining.jsonl $s3_location"
    ]
   },
   {
@@ -1457,26 +1459,12 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 28,
+   "execution_count": null,
    "id": "e4f0ead8-31d2-4146-82c8-2d4d5fa07397",
    "metadata": {
     "tags": []
    },
-   "outputs": [
-    {
-     "ename": "ValidationException",
-     "evalue": "An error occurred (ValidationException) when calling the CreateModelCustomizationJob operation: The provided model identifier is invalid.",
-     "output_type": "error",
-     "traceback": [
-      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
-      "\u001b[0;31mValidationException\u001b[0m                       Traceback (most recent call last)",
-      "Cell \u001b[0;32mIn[28], line 1\u001b[0m\n\u001b[0;32m----> 1\u001b[0m \u001b[43mbedrock_admin\u001b[49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43mcreate_model_customization_job\u001b[49m\u001b[43m(\u001b[49m\n\u001b[1;32m      2\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcustomizationType\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mCONTINUAL_PRE_TRAINING\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\u001b[43m  \u001b[49m\u001b[38;5;66;43;03m# or FINE_TUNING\u001b[39;49;00m\n\u001b[1;32m      3\u001b[0m \u001b[43m    \u001b[49m\u001b[43mjobName\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mjob_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      4\u001b[0m \u001b[43m    \u001b[49m\u001b[43mcustomModelName\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mcustom_model_name\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      5\u001b[0m \u001b[43m    \u001b[49m\u001b[43mroleArn\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mrole\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      6\u001b[0m \u001b[43m    \u001b[49m\u001b[43mbaseModelIdentifier\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43mbase_model_id\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m      7\u001b[0m \u001b[43m    \u001b[49m\u001b[43mhyperParameters\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m \u001b[49m\u001b[43m{\u001b[49m\n\u001b[1;32m      8\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mepochCount\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m10\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m      9\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mbatchSize\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m1\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     10\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlearningRate\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m0.000001\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m,\u001b[49m\n\u001b[1;32m     11\u001b[0m \u001b[43m        \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43mlearningRateWarmupSteps\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43m0\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\n\u001b[1;32m     12\u001b[0m \u001b[43m    \u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     13\u001b[0m \u001b[43m    \u001b[49m\u001b[43mtrainingDataConfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43ms3Uri\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43ms3_location\u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     14\u001b[0m \u001b[43m    \u001b[49m\u001b[43moutputDataConfig\u001b[49m\u001b[38;5;241;43m=\u001b[39;49m\u001b[43m{\u001b[49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[38;5;124;43ms3Uri\u001b[39;49m\u001b[38;5;124;43m\"\u001b[39;49m\u001b[43m:\u001b[49m\u001b[43m \u001b[49m\u001b[43ms3_output\u001b[49m\u001b[43m}\u001b[49m\u001b[43m,\u001b[49m\n\u001b[1;32m     15\u001b[0m \u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/botocore/client.py:535\u001b[0m, in \u001b[0;36mClientCreator._create_api_method.<locals>._api_call\u001b[0;34m(self, *args, **kwargs)\u001b[0m\n\u001b[1;32m    531\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m \u001b[38;5;167;01mTypeError\u001b[39;00m(\n\u001b[1;32m    532\u001b[0m         \u001b[38;5;124mf\u001b[39m\u001b[38;5;124m\"\u001b[39m\u001b[38;5;132;01m{\u001b[39;00mpy_operation_name\u001b[38;5;132;01m}\u001b[39;00m\u001b[38;5;124m() only accepts keyword arguments.\u001b[39m\u001b[38;5;124m\"\u001b[39m\n\u001b[1;32m    533\u001b[0m     )\n\u001b[1;32m    534\u001b[0m \u001b[38;5;66;03m# The \"self\" in this scope is referring to the BaseClient.\u001b[39;00m\n\u001b[0;32m--> 535\u001b[0m \u001b[38;5;28;01mreturn\u001b[39;00m \u001b[38;5;28;43mself\u001b[39;49m\u001b[38;5;241;43m.\u001b[39;49m\u001b[43m_make_api_call\u001b[49m\u001b[43m(\u001b[49m\u001b[43moperation_name\u001b[49m\u001b[43m,\u001b[49m\u001b[43m \u001b[49m\u001b[43mkwargs\u001b[49m\u001b[43m)\u001b[49m\n",
-      "File \u001b[0;32m/opt/conda/lib/python3.10/site-packages/botocore/client.py:980\u001b[0m, in \u001b[0;36mBaseClient._make_api_call\u001b[0;34m(self, operation_name, api_params)\u001b[0m\n\u001b[1;32m    978\u001b[0m     error_code \u001b[38;5;241m=\u001b[39m parsed_response\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mError\u001b[39m\u001b[38;5;124m\"\u001b[39m, {})\u001b[38;5;241m.\u001b[39mget(\u001b[38;5;124m\"\u001b[39m\u001b[38;5;124mCode\u001b[39m\u001b[38;5;124m\"\u001b[39m)\n\u001b[1;32m    979\u001b[0m     error_class \u001b[38;5;241m=\u001b[39m \u001b[38;5;28mself\u001b[39m\u001b[38;5;241m.\u001b[39mexceptions\u001b[38;5;241m.\u001b[39mfrom_code(error_code)\n\u001b[0;32m--> 980\u001b[0m     \u001b[38;5;28;01mraise\u001b[39;00m error_class(parsed_response, operation_name)\n\u001b[1;32m    981\u001b[0m \u001b[38;5;28;01melse\u001b[39;00m:\n\u001b[1;32m    982\u001b[0m     \u001b[38;5;28;01mreturn\u001b[39;00m parsed_response\n",
-      "\u001b[0;31mValidationException\u001b[0m: An error occurred (ValidationException) when calling the CreateModelCustomizationJob operation: The provided model identifier is invalid."
-     ]
-    }
-   ],
+   "outputs": [],
    "source": [
     "bedrock_admin.create_model_customization_job(\n",
     "    customizationType=\"CONTINUAL_PRE_TRAINING\",  # or FINE_TUNING\n",