diff --git a/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/conditional_generation_tf.ipynb b/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/conditional_generation_tf.ipynb
index e2c67eb9..3105e066 100644
--- a/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/conditional_generation_tf.ipynb
+++ b/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/conditional_generation_tf.ipynb
@@ -1039,7 +1039,11 @@
    "cell_type": "code",
    "execution_count": 35,
    "id": "b858cf85-82e6-41ef-905b-d8c5d6fea492",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import os"
@@ -1049,7 +1053,11 @@
    "cell_type": "code",
    "execution_count": 36,
    "id": "05ce7c77-d562-45e8-89bb-cd656aba5a5f",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "%%bash\n",
@@ -1076,7 +1084,11 @@
    "cell_type": "code",
    "execution_count": 37,
    "id": "afd00b7e-8150-4c95-a2e4-037e9c90f92a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1160,7 +1172,9 @@
    "execution_count": 38,
    "id": "1a997c33-5202-466d-8304-b8c30f32978f",
    "metadata": {
-    "tags": []
+    "tags": [
+     "TRITON"
+    ]
    },
    "outputs": [],
    "source": [
@@ -1175,7 +1189,11 @@
    "cell_type": "code",
    "execution_count": 39,
    "id": "9dea1875-6b95-4fc0-926d-a625a441b33d",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "# only use first N examples, since this is slow\n",
@@ -1186,7 +1204,11 @@
    "cell_type": "code",
    "execution_count": 40,
    "id": "5d6c54e7-534d-406f-b8e6-fd592efd0ab2",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "# only use first sentence and add prefix for conditional generation\n",
@@ -1201,7 +1223,11 @@
    "cell_type": "code",
    "execution_count": 41,
    "id": "dc1bbbe3-4232-49e5-80f6-99976524b73b",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "# only use first 100 rows, since generation takes a while\n",
@@ -1212,7 +1238,11 @@
    "cell_type": "code",
    "execution_count": 42,
    "id": "5d10c61c-6102-4d19-8dd6-0c7b5b65343e",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1255,7 +1285,11 @@
    "cell_type": "code",
    "execution_count": 43,
    "id": "2e0907da-a5d9-4c3b-9db4-ce5e70ca9bb4",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "def triton_fn(triton_uri, model_name):\n",
@@ -1305,7 +1339,11 @@
    "cell_type": "code",
    "execution_count": 44,
    "id": "9308bdd7-6f67-484d-8b51-dd1e1b2960ba",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "generate = predict_batch_udf(partial(triton_fn, triton_uri=\"localhost:8001\", model_name=\"hf_generation_tf\"),\n",
@@ -1318,7 +1356,11 @@
    "cell_type": "code",
    "execution_count": 45,
    "id": "38484ffd-370d-492b-8ca4-9eff9f242a9f",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1354,7 +1396,11 @@
    "cell_type": "code",
    "execution_count": 46,
    "id": "ebcb6699-3ac2-4529-ab0f-fab0a5e792da",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1389,7 +1435,11 @@
    "cell_type": "code",
    "execution_count": 47,
    "id": "e2ed18ad-d00b-472c-b2c3-047932f2105d",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1424,7 +1474,11 @@
    "cell_type": "code",
    "execution_count": 48,
    "id": "0cd64a1c-beb8-47d5-ac6f-e8525bb61176",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1481,7 +1535,11 @@
    "cell_type": "code",
    "execution_count": 49,
    "id": "af70fed8-0f2b-4ea7-841c-476afdf9b1c0",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1500,7 +1558,11 @@
    "cell_type": "code",
    "execution_count": 50,
    "id": "ef075e10-e22c-4236-9e0b-cb47cf2d3d06",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1543,7 +1605,11 @@
    "cell_type": "code",
    "execution_count": 51,
    "id": "2e7e4af8-b815-4375-b851-8368309ee8e1",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1578,7 +1644,11 @@
    "cell_type": "code",
    "execution_count": 52,
    "id": "7b0aefb0-a96b-4791-a23c-1ce9b24eb20c",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1613,7 +1683,11 @@
    "cell_type": "code",
    "execution_count": 53,
    "id": "1214b75b-a373-4579-b4c6-0cb8627da776",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1648,7 +1722,11 @@
    "cell_type": "code",
    "execution_count": 54,
    "id": "c9dbd21f-9e37-4221-b765-80ba8c80b884",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1715,7 +1793,11 @@
    "cell_type": "code",
    "execution_count": 55,
    "id": "425d3b28-7705-45ba-8a18-ad34fc895219",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
diff --git a/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/conditional_generation_torch.ipynb b/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/conditional_generation_torch.ipynb
index a09bede3..94cb7df1 100644
--- a/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/conditional_generation_torch.ipynb
+++ b/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/conditional_generation_torch.ipynb
@@ -960,7 +960,11 @@
    "cell_type": "code",
    "execution_count": 28,
    "id": "b858cf85-82e6-41ef-905b-d8c5d6fea492",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import os"
@@ -970,7 +974,11 @@
    "cell_type": "code",
    "execution_count": 29,
    "id": "05ce7c77-d562-45e8-89bb-cd656aba5a5f",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "%%bash\n",
@@ -997,7 +1005,11 @@
    "cell_type": "code",
    "execution_count": 30,
    "id": "afd00b7e-8150-4c95-a2e4-037e9c90f92a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1079,7 +1091,9 @@
    "execution_count": 31,
    "id": "1a997c33-5202-466d-8304-b8c30f32978f",
    "metadata": {
-    "tags": []
+    "tags": [
+     "TRITON"
+    ]
    },
    "outputs": [],
    "source": [
@@ -1094,7 +1108,11 @@
    "cell_type": "code",
    "execution_count": 32,
    "id": "9dea1875-6b95-4fc0-926d-a625a441b33d",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "# only use first N examples, since this is slow\n",
@@ -1105,7 +1123,11 @@
    "cell_type": "code",
    "execution_count": 33,
    "id": "5d6c54e7-534d-406f-b8e6-fd592efd0ab2",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "# only use first sentence and add prefix for conditional generation\n",
@@ -1120,7 +1142,11 @@
    "cell_type": "code",
    "execution_count": 34,
    "id": "dc1bbbe3-4232-49e5-80f6-99976524b73b",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "# only use first 100 rows, since generation takes a while\n",
@@ -1131,7 +1157,11 @@
    "cell_type": "code",
    "execution_count": 35,
    "id": "5d10c61c-6102-4d19-8dd6-0c7b5b65343e",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1174,7 +1204,11 @@
    "cell_type": "code",
    "execution_count": 36,
    "id": "2e0907da-a5d9-4c3b-9db4-ce5e70ca9bb4",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "def triton_fn(triton_uri, model_name):\n",
@@ -1224,7 +1258,11 @@
    "cell_type": "code",
    "execution_count": 37,
    "id": "9308bdd7-6f67-484d-8b51-dd1e1b2960ba",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "generate = predict_batch_udf(partial(triton_fn, triton_uri=\"localhost:8001\", model_name=\"hf_generation_torch\"),\n",
@@ -1237,7 +1275,11 @@
    "cell_type": "code",
    "execution_count": 38,
    "id": "38484ffd-370d-492b-8ca4-9eff9f242a9f",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1273,7 +1315,11 @@
    "cell_type": "code",
    "execution_count": 39,
    "id": "ebcb6699-3ac2-4529-ab0f-fab0a5e792da",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1308,7 +1354,11 @@
    "cell_type": "code",
    "execution_count": 40,
    "id": "e2ed18ad-d00b-472c-b2c3-047932f2105d",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1343,7 +1393,11 @@
    "cell_type": "code",
    "execution_count": 41,
    "id": "0cd64a1c-beb8-47d5-ac6f-e8525bb61176",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1386,7 +1440,11 @@
    "cell_type": "code",
    "execution_count": 42,
    "id": "af70fed8-0f2b-4ea7-841c-476afdf9b1c0",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1405,7 +1463,11 @@
    "cell_type": "code",
    "execution_count": 43,
    "id": "ef075e10-e22c-4236-9e0b-cb47cf2d3d06",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1448,7 +1510,11 @@
    "cell_type": "code",
    "execution_count": 44,
    "id": "2e7e4af8-b815-4375-b851-8368309ee8e1",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1483,7 +1549,11 @@
    "cell_type": "code",
    "execution_count": 45,
    "id": "7b0aefb0-a96b-4791-a23c-1ce9b24eb20c",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1518,7 +1588,11 @@
    "cell_type": "code",
    "execution_count": 46,
    "id": "1214b75b-a373-4579-b4c6-0cb8627da776",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1553,7 +1627,11 @@
    "cell_type": "code",
    "execution_count": 47,
    "id": "c9dbd21f-9e37-4221-b765-80ba8c80b884",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1606,7 +1684,11 @@
    "cell_type": "code",
    "execution_count": 48,
    "id": "425d3b28-7705-45ba-8a18-ad34fc895219",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
diff --git a/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/pipelines_tf.ipynb b/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/pipelines_tf.ipynb
index 115cfffc..dcba0be8 100644
--- a/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/pipelines_tf.ipynb
+++ b/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/pipelines_tf.ipynb
@@ -589,7 +589,11 @@
    "cell_type": "code",
    "execution_count": 22,
    "id": "4d4be844-4b8c-47df-bd09-0c280c7ff16b",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -604,7 +608,11 @@
    "cell_type": "code",
    "execution_count": 23,
    "id": "7e53df9f-43cb-4c38-b8ac-dc2cbad99815",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "%%bash\n",
@@ -631,7 +639,11 @@
    "cell_type": "code",
    "execution_count": 24,
    "id": "144acb8e-4c08-40fc-a9ed-f721c409ee68",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -717,7 +729,11 @@
    "cell_type": "code",
    "execution_count": 25,
    "id": "d53fb283-bf9e-4571-8c68-b75a41f1f067",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "# only use first sentence of IMDB reviews\n",
@@ -732,7 +748,11 @@
    "cell_type": "code",
    "execution_count": 26,
    "id": "29b0cc0d-c480-4e4a-bd41-207dc314cba5",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "def triton_fn(triton_uri, model_name):\n",
@@ -782,7 +802,11 @@
    "cell_type": "code",
    "execution_count": 27,
    "id": "3930cfcd-3284-4c6a-a9b5-36b8053fe899",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "from functools import partial\n",
@@ -800,7 +824,11 @@
    "cell_type": "code",
    "execution_count": 28,
    "id": "8eecbf23-4e9e-4d4c-8645-98209b25db2c",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -837,7 +865,11 @@
    "cell_type": "code",
    "execution_count": 29,
    "id": "566ba28c-0ca4-4479-a24a-c8a362228b89",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -873,7 +905,11 @@
    "cell_type": "code",
    "execution_count": 30,
    "id": "44c7e776-08da-484a-ba07-9d6add1a0f15",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -909,7 +945,11 @@
    "cell_type": "code",
    "execution_count": 31,
    "id": "f61d79f8-661e-4d9e-a3aa-c0754b854603",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -976,7 +1016,11 @@
    "cell_type": "code",
    "execution_count": 32,
    "id": "425d3b28-7705-45ba-8a18-ad34fc895219",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
diff --git a/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/pipelines_torch.ipynb b/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/pipelines_torch.ipynb
index 47f45b67..1e99ed36 100644
--- a/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/pipelines_torch.ipynb
+++ b/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/pipelines_torch.ipynb
@@ -484,7 +484,11 @@
    "cell_type": "code",
    "execution_count": 21,
    "id": "4d4be844-4b8c-47df-bd09-0c280c7ff16b",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -499,7 +503,11 @@
    "cell_type": "code",
    "execution_count": 22,
    "id": "7e53df9f-43cb-4c38-b8ac-dc2cbad99815",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "%%bash\n",
@@ -526,7 +534,11 @@
    "cell_type": "code",
    "execution_count": 23,
    "id": "144acb8e-4c08-40fc-a9ed-f721c409ee68",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -612,7 +624,11 @@
    "cell_type": "code",
    "execution_count": 24,
    "id": "d53fb283-bf9e-4571-8c68-b75a41f1f067",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "# only use first sentence of IMDB reviews\n",
@@ -627,7 +643,11 @@
    "cell_type": "code",
    "execution_count": 25,
    "id": "29b0cc0d-c480-4e4a-bd41-207dc314cba5",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "def triton_fn(triton_uri, model_name):\n",
@@ -677,7 +697,11 @@
    "cell_type": "code",
    "execution_count": 26,
    "id": "3930cfcd-3284-4c6a-a9b5-36b8053fe899",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "from functools import partial\n",
@@ -695,7 +719,11 @@
    "cell_type": "code",
    "execution_count": 27,
    "id": "8eecbf23-4e9e-4d4c-8645-98209b25db2c",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -732,7 +760,11 @@
    "cell_type": "code",
    "execution_count": 28,
    "id": "566ba28c-0ca4-4479-a24a-c8a362228b89",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -768,7 +800,11 @@
    "cell_type": "code",
    "execution_count": 29,
    "id": "44c7e776-08da-484a-ba07-9d6add1a0f15",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -804,7 +840,11 @@
    "cell_type": "code",
    "execution_count": 30,
    "id": "f61d79f8-661e-4d9e-a3aa-c0754b854603",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -857,7 +897,11 @@
    "cell_type": "code",
    "execution_count": 31,
    "id": "425d3b28-7705-45ba-8a18-ad34fc895219",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
diff --git a/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/sentence_transformers_torch.ipynb b/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/sentence_transformers_torch.ipynb
index 4a8a0407..deac314d 100644
--- a/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/sentence_transformers_torch.ipynb
+++ b/examples/ML+DL-Examples/Spark-DL/dl_inference/huggingface/sentence_transformers_torch.ipynb
@@ -444,7 +444,11 @@
    "cell_type": "code",
    "execution_count": 14,
    "id": "772e337e-1098-4c7b-ba81-8cb221a518e2",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -458,7 +462,11 @@
    "cell_type": "code",
    "execution_count": 15,
    "id": "69d0c93a-bb0b-46c5-9d28-7b08a2e70964",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "%%bash\n",
@@ -485,7 +493,11 @@
    "cell_type": "code",
    "execution_count": 16,
    "id": "1654cdc1-4f9a-4fd5-b7ac-6ca4215bde5d",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -566,7 +578,11 @@
    "cell_type": "code",
    "execution_count": 17,
    "id": "2969d502-e97b-49d6-bf80-7d177ae867cf",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "from functools import partial\n",
@@ -579,7 +595,11 @@
    "cell_type": "code",
    "execution_count": 18,
    "id": "c8f1e6d6-6519-49e7-8465-4419547633b8",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -598,7 +618,11 @@
    "cell_type": "code",
    "execution_count": 19,
    "id": "29b0cc0d-c480-4e4a-bd41-207dc314cba5",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "def triton_fn(triton_uri, model_name):\n",
@@ -648,7 +672,11 @@
    "cell_type": "code",
    "execution_count": 20,
    "id": "9c712b8f-6eb4-4fb8-9f0a-04feef847fea",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "encode = predict_batch_udf(partial(triton_fn, triton_uri=\"localhost:8001\", model_name=\"hf_transformer_torch\"),\n",
@@ -661,7 +689,11 @@
    "cell_type": "code",
    "execution_count": 21,
    "id": "934c1a1f-b126-45b0-9c15-265236820ad3",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -683,7 +715,11 @@
    "cell_type": "code",
    "execution_count": 22,
    "id": "f84cd3f6-b6a8-4142-859a-91f3c183457b",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -704,7 +740,11 @@
    "cell_type": "code",
    "execution_count": 23,
    "id": "921a4c01-e296-4406-be90-86f20c8c582d",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -725,7 +765,11 @@
    "cell_type": "code",
    "execution_count": 24,
    "id": "9f67584e-9c4e-474f-b6ea-7811b14d116e",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -778,7 +822,11 @@
    "cell_type": "code",
    "execution_count": 25,
    "id": "d8e5466b-b5dc-4fe1-9012-0c87cdd72962",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
diff --git a/examples/ML+DL-Examples/Spark-DL/dl_inference/pytorch/image_classification_torch.ipynb b/examples/ML+DL-Examples/Spark-DL/dl_inference/pytorch/image_classification_torch.ipynb
index ea07ce28..b6d739a3 100644
--- a/examples/ML+DL-Examples/Spark-DL/dl_inference/pytorch/image_classification_torch.ipynb
+++ b/examples/ML+DL-Examples/Spark-DL/dl_inference/pytorch/image_classification_torch.ipynb
@@ -2007,7 +2007,11 @@
    "cell_type": "code",
    "execution_count": 57,
    "id": "53ca290a-ccc3-4923-a292-944921bab36d",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -2022,7 +2026,11 @@
    "cell_type": "code",
    "execution_count": 58,
    "id": "8fa92fe4-2e04-4d82-a357-bfdfca38bd8c",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "%%bash\n",
@@ -2047,7 +2055,11 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "5e869730-3597-4074-bab0-f87768f8996a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "num_executors = 1\n",
@@ -2103,7 +2115,11 @@
    "cell_type": "code",
    "execution_count": 60,
    "id": "ab94d4d1-dac6-4474-9eb0-59478aa98f7d",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "data": {
@@ -2126,7 +2142,10 @@
    "execution_count": 61,
    "id": "12b5f2fc-52e9-428a-b683-6ab1b639aa24",
    "metadata": {
-    "scrolled": true
+    "scrolled": true,
+    "tags": [
+     "TRITON"
+    ]
    },
    "outputs": [
     {
@@ -2148,7 +2167,11 @@
    "cell_type": "code",
    "execution_count": 62,
    "id": "960657d0-31c9-4df6-8eb8-ac3d23137f7a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "def triton_fn(triton_uri, model_name):\n",
@@ -2198,7 +2221,11 @@
    "cell_type": "code",
    "execution_count": 63,
    "id": "0262fd4a-9845-44b9-8c75-1c105e7deeca",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "mnist = predict_batch_udf(partial(triton_fn, triton_uri=\"localhost:8001\", model_name=\"fashion_mnist\"),\n",
@@ -2211,7 +2238,11 @@
    "cell_type": "code",
    "execution_count": 64,
    "id": "fc5f6baa-052e-4b89-94b6-4821cf01952a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2231,7 +2262,11 @@
    "cell_type": "code",
    "execution_count": 65,
    "id": "a85dea35-e41d-482d-8a8f-52d3c108f038",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2251,7 +2286,11 @@
    "cell_type": "code",
    "execution_count": 66,
    "id": "bc3f0dbe-c52b-41d6-8097-8cebaa5ee5a8",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2271,7 +2310,11 @@
    "cell_type": "code",
    "execution_count": 67,
    "id": "99fb5e8d",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2318,7 +2361,11 @@
    "cell_type": "code",
    "execution_count": null,
    "id": "ab2fe42f-a072-4370-bac2-52fd95363530",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "def stop_triton(it):\n",
diff --git a/examples/ML+DL-Examples/Spark-DL/dl_inference/pytorch/regression_torch.ipynb b/examples/ML+DL-Examples/Spark-DL/dl_inference/pytorch/regression_torch.ipynb
index 5ccc22ec..3412f91a 100644
--- a/examples/ML+DL-Examples/Spark-DL/dl_inference/pytorch/regression_torch.ipynb
+++ b/examples/ML+DL-Examples/Spark-DL/dl_inference/pytorch/regression_torch.ipynb
@@ -2273,7 +2273,11 @@
    "cell_type": "code",
    "execution_count": 73,
    "id": "a9ab4cdf-8103-447e-9ac8-944e2e527239",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -2288,7 +2292,11 @@
    "cell_type": "code",
    "execution_count": 74,
    "id": "6632636e-67a3-406c-832c-758aac4245fd",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "%%bash\n",
@@ -2313,7 +2321,10 @@
    "execution_count": 75,
    "id": "c6fd1612-de6a-461c-a2ad-1a3fcd277d66",
    "metadata": {
-    "scrolled": true
+    "scrolled": true,
+    "tags": [
+     "TRITON"
+    ]
    },
    "outputs": [
     {
@@ -2388,7 +2399,11 @@
    "cell_type": "code",
    "execution_count": 76,
    "id": "5eae04bc-75ca-421a-87c8-ac507ce1f2f5",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "df = spark.read.parquet(\"california_housing\")"
@@ -2399,7 +2414,9 @@
    "execution_count": 77,
    "id": "b350bd8e-9b8f-4511-9ddf-76d917b21b5f",
    "metadata": {
-    "tags": []
+    "tags": [
+     "TRITON"
+    ]
    },
    "outputs": [
     {
@@ -2429,7 +2446,11 @@
    "cell_type": "code",
    "execution_count": 78,
    "id": "69b343ec-688d-4e4d-985e-db72beaaf00c",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "def triton_fn(triton_uri, model_name):\n",
@@ -2479,7 +2500,11 @@
    "cell_type": "code",
    "execution_count": 79,
    "id": "d3e64fda-117b-4810-a9a2-dd498239496f",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "classify = predict_batch_udf(partial(triton_fn, triton_uri=\"localhost:8001\", model_name=\"housing_model\"),\n",
@@ -2492,7 +2517,11 @@
    "cell_type": "code",
    "execution_count": 80,
    "id": "a24149a5-3adc-4089-8769-13cf1e44547a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2514,7 +2543,11 @@
    "cell_type": "code",
    "execution_count": 81,
    "id": "df2ce39f-30af-491a-8472-800fb1ce8458",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2535,7 +2568,11 @@
    "cell_type": "code",
    "execution_count": 82,
    "id": "ca6f3eaa-9569-45d0-88bf-9aa0757e1ecb",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "# should raise ValueError\n",
@@ -2548,7 +2585,9 @@
    "execution_count": 83,
    "id": "b79c62c8-e1e8-4467-8aef-8939c31833b8",
    "metadata": {
-    "tags": []
+    "tags": [
+     "TRITON"
+    ]
    },
    "outputs": [
     {
@@ -2602,7 +2641,11 @@
    "cell_type": "code",
    "execution_count": 84,
    "id": "15e9b3df-f3c9-46bb-bbeb-42496f7663de",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
diff --git a/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/feature_columns_tf.ipynb b/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/feature_columns_tf.ipynb
index 17af1c93..2ff37b6c 100644
--- a/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/feature_columns_tf.ipynb
+++ b/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/feature_columns_tf.ipynb
@@ -23,7 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "01162f42-0637-4dfe-8d7d-b577e4ffd017",
    "metadata": {},
    "outputs": [
@@ -31,13 +31,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-10-03 17:38:52.548855: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
-      "2024-10-03 17:38:52.555529: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
-      "2024-10-03 17:38:52.563119: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
-      "2024-10-03 17:38:52.565499: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
-      "2024-10-03 17:38:52.571252: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "2024-10-24 16:04:17.711230: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
+      "2024-10-24 16:04:17.719701: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+      "2024-10-24 16:04:17.728758: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+      "2024-10-24 16:04:17.731459: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+      "2024-10-24 16:04:17.738797: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
       "To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
-      "2024-10-03 17:38:52.894224: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
+      "2024-10-24 16:04:18.115892: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
      ]
     }
    ],
@@ -51,7 +51,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "9fa3e1b7-58cd-45f9-9fee-85f25a31c3c6",
    "metadata": {},
    "outputs": [
@@ -78,22 +78,29 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 7,
    "id": "9326b072-a53c-40c4-a6cb-bd4d3d644d03",
    "metadata": {},
    "outputs": [],
    "source": [
+    "import pathlib\n",
+    "import os\n",
     "dataset_url = 'http://storage.googleapis.com/download.tensorflow.org/data/petfinder-mini.zip'\n",
-    "csv_file = 'datasets/petfinder-mini/petfinder-mini.csv'\n",
     "\n",
-    "tf.keras.utils.get_file('petfinder_mini.zip', dataset_url,\n",
-    "                        extract=True, cache_dir='.')\n",
-    "dataframe = pd.read_csv(csv_file)"
+    "data_dir = tf.keras.utils.get_file('petfinder_mini.zip', dataset_url, extract=True, cache_dir='.')\n",
+    "data_dir = pathlib.Path(data_dir)\n",
+    "try:\n",
+    "    # pet-finder-mini might be under a parent a directory petfinder_mini_extracted. Check if this is the case:\n",
+    "    dataset = os.path.join(os.path.dirname(data_dir), 'petfinder_mini_extracted/petfinder-mini/petfinder-mini.csv')\n",
+    "    dataframe = pd.read_csv(dataset)\n",
+    "except:\n",
+    "    dataset = os.path.join(os.path.dirname(data_dir), 'petfinder-mini/petfinder-mini.csv')\n",
+    "    dataframe = pd.read_csv(dataset)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 11,
    "id": "e98480ef-d13d-44c0-a227-e9a22f9bf2b0",
    "metadata": {},
    "outputs": [
@@ -253,7 +260,7 @@
        "4  This handsome yet cute boy is up for adoption....         3              2  "
       ]
      },
-     "execution_count": 5,
+     "execution_count": 11,
      "metadata": {},
      "output_type": "execute_result"
     }
@@ -1267,7 +1274,11 @@
    "cell_type": "code",
    "execution_count": 45,
    "id": "2605d134-ef75-4d94-9b16-2c6d85f29bef",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -1281,7 +1292,11 @@
    "cell_type": "code",
    "execution_count": 46,
    "id": "4666e618-8038-4dc5-9be7-793aedbf4500",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1316,7 +1331,10 @@
    "execution_count": 47,
    "id": "a7fb146c-5319-4831-85f7-f2f3c084b042",
    "metadata": {
-    "scrolled": true
+    "scrolled": true,
+    "tags": [
+     "TRITON"
+    ]
    },
    "outputs": [
     {
@@ -1395,7 +1413,11 @@
    "cell_type": "code",
    "execution_count": 48,
    "id": "fe8dc3e6-f1b1-4a24-85f4-0a5ecabef4c5",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "df = spark.read.parquet(\"datasets/petfinder-mini\")"
@@ -1405,7 +1427,11 @@
    "cell_type": "code",
    "execution_count": 49,
    "id": "ce92f041-930f-48ed-9a03-19f6c249ca27",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1433,7 +1459,11 @@
    "cell_type": "code",
    "execution_count": 50,
    "id": "4cfb3f34-a215-4781-91bf-2bec85e15633",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1454,7 +1484,9 @@
    "id": "b315ee72-62af-476b-a994-0dba72d5f96e",
    "metadata": {
     "scrolled": true,
-    "tags": []
+    "tags": [
+     "TRITON"
+    ]
    },
    "outputs": [
     {
@@ -1475,7 +1507,11 @@
    "cell_type": "code",
    "execution_count": 52,
    "id": "da004eca-f7ad-4ee3-aa88-a6a20c1b72e5",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "def triton_fn(triton_uri, model_name):\n",
@@ -1545,7 +1581,11 @@
    "cell_type": "code",
    "execution_count": 53,
    "id": "2ffb020e-dc93-456b-bee6-405611eee1e1",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "from functools import partial\n",
@@ -1561,7 +1601,11 @@
    "cell_type": "code",
    "execution_count": 54,
    "id": "7657f820-5ec2-4ac8-a107-4b58773d204a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1597,7 +1641,7 @@
     }
    ],
    "source": [
-    "# FAILS: Op type not registered 'DenseBincount' WITHOUT custom python backend\n",
+    "# WITHOUT custom python backend, FAILS with: Op type not registered 'DenseBincount' \n",
     "df.withColumn(\"preds\", classify(struct(*columns))).show(truncate=10)"
    ]
   },
@@ -1605,7 +1649,11 @@
    "cell_type": "code",
    "execution_count": 55,
    "id": "e6ff0356-becd-421f-aebb-272497d5ad6a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1633,7 +1681,11 @@
    "cell_type": "code",
    "execution_count": 56,
    "id": "ce18ee7c-5958-4986-b200-6d986fcc6243",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1669,7 +1721,9 @@
    "execution_count": 57,
    "id": "0888ce40-b2c4-4aed-8ccb-6a8bcd00abc8",
    "metadata": {
-    "tags": []
+    "tags": [
+     "TRITON"
+    ]
    },
    "outputs": [
     {
@@ -1698,7 +1752,11 @@
    "cell_type": "code",
    "execution_count": 58,
    "id": "d45812b5-f584-41a4-a821-2b59e065671c",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1751,7 +1809,11 @@
    "cell_type": "code",
    "execution_count": 59,
    "id": "6914f44f-677f-4db3-be09-783df8d11b8a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
diff --git a/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/image_classification_tf.ipynb b/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/image_classification_tf.ipynb
index 5add2686..f7df9f51 100644
--- a/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/image_classification_tf.ipynb
+++ b/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/image_classification_tf.ipynb
@@ -1950,7 +1950,11 @@
    "cell_type": "code",
    "execution_count": 52,
    "id": "a64d19b1-ba4a-4dc7-b3a9-368dc47d0fd8",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import os\n",
@@ -1963,7 +1967,11 @@
    "cell_type": "code",
    "execution_count": 53,
    "id": "8fa92fe4-2e04-4d82-a357-bfdfca38bd8c",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "%%bash\n",
@@ -1988,7 +1996,11 @@
    "cell_type": "code",
    "execution_count": 54,
    "id": "0f7ecb25-be16-40c4-bdbb-441e2f537000",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -2055,7 +2067,11 @@
    "cell_type": "code",
    "execution_count": 55,
    "id": "43b93753-1d52-4060-9986-f24c30a67528",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "data": {
@@ -2085,7 +2101,11 @@
    "cell_type": "code",
    "execution_count": 56,
    "id": "3af08bd0-3838-4769-a8de-2643db4101c6",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "def triton_fn(triton_uri, model_name):\n",
@@ -2135,7 +2155,11 @@
    "cell_type": "code",
    "execution_count": 57,
    "id": "6658d2a1-ef7b-4ca1-9fb6-f2ac9050f3e5",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "from functools import partial\n",
@@ -2150,7 +2174,11 @@
    "cell_type": "code",
    "execution_count": 58,
    "id": "8397aa14-82fd-4351-a477-dc8e8b321fa2",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2170,7 +2198,11 @@
    "cell_type": "code",
    "execution_count": 59,
    "id": "82698bd9-377a-4415-8971-835487f876cc",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2190,7 +2222,11 @@
    "cell_type": "code",
    "execution_count": 60,
    "id": "419ad7bd-fa28-49d3-b98d-db9fba5aeaef",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -2321,7 +2357,11 @@
    "cell_type": "code",
    "execution_count": 61,
    "id": "79d90a26",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import matplotlib.pyplot as plt\n",
@@ -2332,7 +2372,11 @@
    "cell_type": "code",
    "execution_count": 62,
    "id": "4ca495f5",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "sample = preds.iloc[0]\n",
@@ -2346,7 +2390,11 @@
    "cell_type": "code",
    "execution_count": 63,
    "id": "a5d10903",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "data": {
@@ -2380,7 +2428,11 @@
    "cell_type": "code",
    "execution_count": 64,
    "id": "9c9fd967-5cd9-4265-add9-db5c1ccf9893",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
diff --git a/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/keras-metadata_tf.ipynb b/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/keras-metadata_tf.ipynb
index e0683e38..007f6d8a 100644
--- a/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/keras-metadata_tf.ipynb
+++ b/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/keras-metadata_tf.ipynb
@@ -768,7 +768,11 @@
    "cell_type": "code",
    "execution_count": 29,
    "id": "2605d134-ef75-4d94-9b16-2c6d85f29bef",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import os\n",
@@ -781,7 +785,11 @@
    "cell_type": "code",
    "execution_count": 30,
    "id": "4666e618-8038-4dc5-9be7-793aedbf4500",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "%%bash\n",
@@ -806,7 +814,11 @@
    "cell_type": "code",
    "execution_count": 31,
    "id": "8c8c0744-0558-4dac-bbfe-8bdde4b2af2d",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -880,7 +892,11 @@
    "cell_type": "code",
    "execution_count": 32,
    "id": "bcd46360-6851-4a9d-8590-c086e001242a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "def triton_fn(triton_uri, model_name):\n",
@@ -931,7 +947,11 @@
    "cell_type": "code",
    "execution_count": 33,
    "id": "9fabcaeb-5a44-42bb-8097-5dbc2d0cee3e",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "from functools import partial\n",
@@ -946,7 +966,11 @@
    "cell_type": "code",
    "execution_count": 34,
    "id": "b17f33c8-a0f0-4bce-91f8-5838ba9b12a7",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "# spark.conf.set(\"spark.sql.execution.arrow.maxRecordsPerBatch\", \"1024\")\n",
@@ -957,7 +981,11 @@
    "cell_type": "code",
    "execution_count": 35,
    "id": "8e5b9e99-a1cf-43d3-a795-c7271a917057",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "df = spark.read.parquet(\"image_data.parquet\")"
@@ -968,7 +996,9 @@
    "execution_count": 36,
    "id": "e595473d-1a5d-46a6-a6ba-89d2ea903de9",
    "metadata": {
-    "tags": []
+    "tags": [
+     "TRITON"
+    ]
    },
    "outputs": [
     {
@@ -1031,7 +1061,11 @@
    "cell_type": "code",
    "execution_count": 37,
    "id": "5f66d468-e0b1-4589-8606-b3848063a823",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1092,7 +1126,11 @@
    "cell_type": "code",
    "execution_count": 38,
    "id": "632c4c3a-fa52-4c3d-b71e-7526286e353a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1137,7 +1175,11 @@
    "cell_type": "code",
    "execution_count": 39,
    "id": "bbfcaa51-3b9f-43ff-a4a8-4b46766115b8",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
diff --git a/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/text_classification_tf.ipynb b/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/text_classification_tf.ipynb
index 971bf393..63499611 100644
--- a/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/text_classification_tf.ipynb
+++ b/examples/ML+DL-Examples/Spark-DL/dl_inference/tensorflow/text_classification_tf.ipynb
@@ -23,7 +23,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 2,
+   "execution_count": 1,
    "id": "76f0f5df-502f-444e-b2ee-1122e1dea870",
    "metadata": {},
    "outputs": [
@@ -31,13 +31,13 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-10-03 17:43:56.140645: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
-      "2024-10-03 17:43:56.147227: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
-      "2024-10-03 17:43:56.154601: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
-      "2024-10-03 17:43:56.156763: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
-      "2024-10-03 17:43:56.162424: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
+      "2024-10-24 16:15:43.020721: I tensorflow/core/util/port.cc:153] oneDNN custom operations are on. You may see slightly different numerical results due to floating-point round-off errors from different computation orders. To turn them off, set the environment variable `TF_ENABLE_ONEDNN_OPTS=0`.\n",
+      "2024-10-24 16:15:43.028070: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:485] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered\n",
+      "2024-10-24 16:15:43.035674: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:8454] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered\n",
+      "2024-10-24 16:15:43.037910: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1452] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered\n",
+      "2024-10-24 16:15:43.044256: I tensorflow/core/platform/cpu_feature_guard.cc:210] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations.\n",
       "To enable the following instructions: AVX2 AVX_VNNI FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags.\n",
-      "2024-10-03 17:43:56.485452: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
+      "2024-10-24 16:15:43.368732: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT\n"
      ]
     }
    ],
@@ -54,7 +54,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 3,
+   "execution_count": 2,
    "id": "a364ad5f-b269-45b5-ab8b-d8f34fb642b7",
    "metadata": {},
    "outputs": [
@@ -72,7 +72,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 4,
+   "execution_count": 3,
    "id": "57b1d71f",
    "metadata": {},
    "outputs": [],
@@ -89,27 +89,42 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 5,
+   "execution_count": 10,
    "id": "d229c1b6-3967-46b5-9ea8-68f4b42dd211",
    "metadata": {},
+   "outputs": [],
+   "source": [
+    "import pathlib\n",
+    "url = \"https://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz\"\n",
+    "\n",
+    "dataset = tf.keras.utils.get_file(\n",
+    "    fname=\"aclImdb\", origin=url, untar=True,\n",
+    ")\n",
+    "\n",
+    "dataset_dir = pathlib.Path(dataset)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "id": "bfa5177f",
+   "metadata": {},
    "outputs": [
     {
      "name": "stdout",
      "output_type": "stream",
      "text": [
-      "Downloading data from https://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz\n",
-      "\u001b[1m84125825/84125825\u001b[0m \u001b[32m━━━━━━━━━━━━━━━━━━━━\u001b[0m\u001b[37m\u001b[0m \u001b[1m4s\u001b[0m 0us/step\n"
+      "/home/rishic/.keras/datasets/aclImdb\n",
+      "/home/rishic/.keras/datasets/aclImdb\n"
      ]
     }
    ],
    "source": [
-    "url = \"https://ai.stanford.edu/~amaas/data/sentiment/aclImdb_v1.tar.gz\"\n",
-    "\n",
-    "dataset = tf.keras.utils.get_file(\n",
-    "    \"aclImdb_v1\", url, untar=True, cache_dir=\".\", cache_subdir=\"\"\n",
-    ")\n",
-    "\n",
-    "dataset_dir = os.path.join(os.path.dirname(dataset), \"aclImdb\")"
+    "print(dataset_dir)\n",
+    "# aclImdb might be created as a directory containing a single directory aclImdb. Check if this is the case:\n",
+    "if os.path.exists(dataset_dir / \"aclImdb\"):\n",
+    "    dataset_dir = dataset_dir / \"aclImdb\"\n",
+    "print(dataset_dir)"
    ]
   },
   {
@@ -135,7 +150,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 7,
+   "execution_count": 13,
    "id": "12faaa3f-3441-4361-b9eb-4317e8c2c2f7",
    "metadata": {},
    "outputs": [
@@ -152,19 +167,20 @@
        " 'unsup']"
       ]
      },
-     "execution_count": 7,
+     "execution_count": 13,
      "metadata": {},
      "output_type": "execute_result"
     }
    ],
    "source": [
     "train_dir = os.path.join(dataset_dir, \"train\")\n",
+    "test_dir = os.path.join(dataset_dir, \"test\")\n",
     "os.listdir(train_dir)"
    ]
   },
   {
    "cell_type": "code",
-   "execution_count": 8,
+   "execution_count": 14,
    "id": "152cc0cc-65d0-4e17-9ee8-222390df45b5",
    "metadata": {},
    "outputs": [
@@ -184,7 +200,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 9,
+   "execution_count": 15,
    "id": "b2277f58-78c8-4a12-bc98-5103e7c81a35",
    "metadata": {},
    "outputs": [],
@@ -195,7 +211,7 @@
   },
   {
    "cell_type": "code",
-   "execution_count": 10,
+   "execution_count": 17,
    "id": "ed83de92-ebb3-4170-b2bf-25265c6a6942",
    "metadata": {},
    "outputs": [
@@ -211,7 +227,7 @@
      "name": "stderr",
      "output_type": "stream",
      "text": [
-      "2024-10-03 17:44:07.678162: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 44790 MB memory:  -> device: 0, name: NVIDIA RTX A6000, pci bus id: 0000:01:00.0, compute capability: 8.6\n"
+      "2024-10-24 02:18:45.343343: I tensorflow/core/common_runtime/gpu/gpu_device.cc:2021] Created device /job:localhost/replica:0/task:0/device:GPU:0 with 46446 MB memory:  -> device: 0, name: NVIDIA RTX A6000, pci bus id: 0000:01:00.0, compute capability: 8.6\n"
      ]
     }
    ],
@@ -220,7 +236,7 @@
     "seed = 42\n",
     "\n",
     "raw_train_ds = tf.keras.utils.text_dataset_from_directory(\n",
-    "    \"aclImdb/train\",\n",
+    "    train_dir,\n",
     "    batch_size=batch_size,\n",
     "    validation_split=0.2,\n",
     "    subset=\"training\",\n",
@@ -298,7 +314,7 @@
    ],
    "source": [
     "raw_val_ds = tf.keras.utils.text_dataset_from_directory(\n",
-    "    \"aclImdb/train\",\n",
+    "    train_dir,\n",
     "    batch_size=batch_size,\n",
     "    validation_split=0.2,\n",
     "    subset=\"validation\",\n",
@@ -322,7 +338,7 @@
    ],
    "source": [
     "raw_test_ds = tf.keras.utils.text_dataset_from_directory(\n",
-    "    \"aclImdb/test\", batch_size=batch_size\n",
+    "    test_dir, batch_size=batch_size\n",
     ")"
    ]
   },
@@ -1374,7 +1390,11 @@
    "cell_type": "code",
    "execution_count": 47,
    "id": "772e337e-1098-4c7b-ba81-8cb221a518e2",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import numpy as np\n",
@@ -1388,7 +1408,11 @@
    "cell_type": "code",
    "execution_count": 48,
    "id": "69d0c93a-bb0b-46c5-9d28-7b08a2e70964",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "%%bash\n",
@@ -1405,7 +1429,11 @@
    "cell_type": "code",
    "execution_count": 49,
    "id": "f4f14c8f",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "import unicodedata\n",
@@ -1444,7 +1472,11 @@
    "cell_type": "code",
    "execution_count": 50,
    "id": "a7fb146c-5319-4831-85f7-f2f3c084b042",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",
@@ -1522,7 +1554,11 @@
    "cell_type": "code",
    "execution_count": 51,
    "id": "41106a02-236e-4cb3-ac51-76aa64b663c2",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1574,7 +1610,11 @@
    "cell_type": "code",
    "execution_count": 52,
    "id": "8b763167-7f50-4278-9bc9-6c3433b62294",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "data": {
@@ -1596,7 +1636,11 @@
    "cell_type": "code",
    "execution_count": 53,
    "id": "29b0cc0d-c480-4e4a-bd41-207dc314cba5",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "def triton_fn(triton_uri, model_name):\n",
@@ -1646,7 +1690,11 @@
    "cell_type": "code",
    "execution_count": 54,
    "id": "8e06d33f-5cef-4a48-afc3-5d468f8ec2b4",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [],
    "source": [
     "from functools import partial\n",
@@ -1661,7 +1709,11 @@
    "cell_type": "code",
    "execution_count": 55,
    "id": "d89e74ad-e551-4bfa-ad08-98725878630a",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1714,7 +1766,11 @@
    "cell_type": "code",
    "execution_count": 56,
    "id": "b4fa7fc9-341c-49a6-9af2-e316f2355d67",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stdout",
@@ -1770,7 +1826,11 @@
    "cell_type": "code",
    "execution_count": 57,
    "id": "a71ac9b6-47a2-4306-bc40-9ce7b4e968ec",
-   "metadata": {},
+   "metadata": {
+    "tags": [
+     "TRITON"
+    ]
+   },
    "outputs": [
     {
      "name": "stderr",