Update model_garden_pytorch_llama3_1_finetuning.ipynb

Author: gurusai-voleti

notebooks/community/model_garden/model_garden_pytorch_llama3_1_finetuning.ipynb

@@ -188,7 +188,7 @@
         "    ! gsutil mb -l {REGION} {BUCKET_URI}\n",
         "else:\n",
         "    assert BUCKET_URI.startswith(\"gs://\"), \"BUCKET_URI must start with `gs://`.\"\n",
-        "    shell_output = ! gsutil ls -b {BUCKET_NAME} | grep \"Location constraint:\" | sed \"s/Location constraint://\"\n",
+        "    shell_output = ! gsutil ls -Lb {BUCKET_NAME} | grep \"Location constraint:\" | sed \"s/Location constraint://\"\n",
         "    bucket_region = shell_output[0].strip().lower()\n",
         "    if bucket_region != REGION:\n",
         "        raise ValueError(\n",
@@ -239,9 +239,7 @@
         "\n",
         "# @markdown **Only select and fill one of the following sections.**\n",
         "# It is recommended to use \"Google Cloud\" for 405B model since it can be downloaded faster.\n",
-        "LOAD_MODEL_FROM = (\n",
-        "    \"Google Cloud\"  # @param [\"Hugging Face\", \"Google Cloud\"] {isTemplate:true}\n",
-        ")\n",
+        "LOAD_MODEL_FROM = \"Google Cloud\"  # @param [\"Hugging Face\", \"Google Cloud\"] {isTemplate:true}\n",
         "\n",
         "# @markdown ---\n",
         "\n",
@@ -451,9 +449,7 @@
         "# @markdown 1. If `max_steps > 0`, it takes precedence over `epochs`. One can set a small `max_steps` value to quickly check the pipeline.\n",
         "\n",
         "# @markdown Acceletor type to use for training.\n",
-        "training_accelerator_type = (\n",
-        "    \"NVIDIA_A100_80GB\"  # @param [\"NVIDIA_A100_80GB\", \"NVIDIA_H100_80GB\"]\n",
-        ")\n",
+        "training_accelerator_type = \"NVIDIA_A100_80GB\"  # @param [\"NVIDIA_A100_80GB\", \"NVIDIA_H100_80GB\"]\n",
         "\n",
         "# The pre-built training docker image.\n",
         "if training_accelerator_type == \"NVIDIA_A100_80GB\":\n",