Replace internal S3 URIs with user placeholders in SFT notebook

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>

Author: JiwaniZakir

v3-examples/model-customization-examples/sft_finetuning_example_notebook_pysdk_prod_v3.ipynb

@@ -85,13 +85,19 @@
     "from sagemaker.ai_registry.dataset_utils import CustomizationTechnique\n",
     "\n",
     "\n",
-    "\n",
     "# Register dataset in SageMaker AI Registry\n",
     "# This creates a versioned dataset that can be referenced by ARN\n",
-    "# Provide a source (it can be local file path or S3 URL)\n",
+    "# Provide a source: a local file path or your own S3 URI pointing to a JSONL file.\n",
+    "# The dataset must be in JSONL format with each line containing a JSON object\n",
+    "# with 'prompt' and 'completion' fields. See the SageMaker documentation for details:\n",
+    "# https://docs.aws.amazon.com/sagemaker/latest/dg/model-customize-sft.html\n",
+    "#\n",
+    "# Replace the placeholder below with your own S3 URI or local file path:\n",
+    "MY_DATASET_S3_URI = \"s3://<your-bucket>/<path-to-your-dataset>.jsonl\"  # TODO: replace with your dataset URI\n",
+    "\n",
     "dataset = DataSet.create(\n",
     "    name=\"demo-1\",\n",
-    "    source=\"s3://mc-flows-sdk-testing/input_data/sft/sample_data_256_final.jsonl\"\n",
+    "    source=MY_DATASET_S3_URI\n",
     ")\n",
     "\n",
     "print(f\"Dataset ARN: {dataset.arn}\")"
@@ -163,7 +169,7 @@
     "    mlflow_experiment_name=\"test-finetuned-models-exp\", \n",
     "    mlflow_run_name=\"test-finetuned-models-run\", \n",
     "    training_dataset=dataset.arn, \n",
-    "    s3_output_path=\"s3://mc-flows-sdk-testing/output/\",\n",
+    "    s3_output_path=\"s3://<your-bucket>/output/\",  # TODO: replace with your S3 output path\n",
     "    accept_eula=True\n",
     ")\n"
    ]
@@ -378,7 +384,7 @@
     "    mlflow_experiment_name=\"test-finetuned-models-exp\", # Optional[str]\n",
     "    mlflow_run_name=\"test-finetuned-models-run\", # Optional[str]\n",
     "    training_dataset=dataset.arn, #Optional[]\n",
-    "    s3_output_path=\"s3://mc-flows-sdk-testing/output/\",\n",
+    "    s3_output_path=\"s3://<your-bucket>/output/\",  # TODO: replace with your S3 output path\n",
     ")\n"
    ]
   },
@@ -439,7 +445,7 @@
     "    mlflow_experiment_name=\"test-nova-finetuned-models-exp\", \n",
     "    mlflow_run_name=\"test-nova-finetuned-models-run\", \n",
     "    training_dataset=\"arn:aws:sagemaker:us-east-1:<>:hub-content/sdktest/DataSet/sft-nova-test-dataset/0.0.1\",\n",
-    "    s3_output_path=\"s3://mc-flows-sdk-testing-us-east-1/output/\"\n",
+    "    s3_output_path=\"s3://<your-bucket>/output/\"  # TODO: replace with your S3 output path\n",
     ")\n"
    ]
   },
@@ -487,4 +493,4 @@
  },
  "nbformat": 4,
  "nbformat_minor": 5
-}
+}