diff --git a/training/distributed_training/pytorch/model_parallel/gpt-j/11_train_gptj_smp_tensor_parallel_notebook.ipynb b/training/distributed_training/pytorch/model_parallel/gpt-j/11_train_gptj_smp_tensor_parallel_notebook.ipynb
index 7f67abd03d..516d06bf7f 100644
--- a/training/distributed_training/pytorch/model_parallel/gpt-j/11_train_gptj_smp_tensor_parallel_notebook.ipynb
+++ b/training/distributed_training/pytorch/model_parallel/gpt-j/11_train_gptj_smp_tensor_parallel_notebook.ipynb
@@ -11,7 +11,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "This notebook walks you through how to use the tensor parallelism feature provided by the SageMaker model parallelism library. You'll learn how to train the GPT-J model with tensor parallelism on the GLUE sst2 dataset.\n",
+    "This notebook walks you through how to use the tensor parallelism feature provided by the SageMaker model parallelism library. You'll learn how to run FP16 training of the GPT-J model with tensor parallelism on the GLUE sst2 dataset.\n",
     "\n",
     "## Install and Upgrade Libraries\n",
     "\n",
@@ -810,7 +810,7 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Create a SageMaker HuggingFace 🤗 Estimator\n",
+    "### Create a SageMaker PyTorch Estimator\n",
     "\n",
     "The following cell constructs a PyTorch estimator using the parameters defined above. To see how the SageMaker tensor parallelism modules and functions are applied to the script, see the `train_gptj_smp_tensor_parallel_script.py` file and the private preview documentation. "
    ]
diff --git a/training/distributed_training/pytorch/model_parallel/gpt2/smp-train-gpt-simple.ipynb b/training/distributed_training/pytorch/model_parallel/gpt2/smp-train-gpt-simple.ipynb
index 26ef87196f..861fa5b2bd 100644
--- a/training/distributed_training/pytorch/model_parallel/gpt2/smp-train-gpt-simple.ipynb
+++ b/training/distributed_training/pytorch/model_parallel/gpt2/smp-train-gpt-simple.ipynb
@@ -23,7 +23,7 @@
     "- `requirements.txt`: This will install the dependencies, like the right version of huggingface transformers.\n",
     "- `data_prep_512.py`: This will download and preprocess the openwebtext dataset.\n",
     "- `memory_tracker.py`: This contains the functions to track memory usage.\n",
-    "- `sharded_data_parallel_checkpoint.py`: This contains the checkpoint utils for sharded dat parallelism\n",
+    "- `sharded_data_parallel_checkpoint.py`: This contains checkpoint util functions for sharded data parallelism\n",
     "\n",
     "### Additional Resources\n",
     "If you are a new user of Amazon SageMaker, you may find the following helpful to learn more about SMP and using SageMaker with PyTorch.\n",
@@ -528,9 +528,9 @@
    "cell_type": "markdown",
    "metadata": {},
    "source": [
-    "### Create a SageMaker HuggingFace Estimator\n",
+    "### Create a SageMaker PyTorch Estimator\n",
     "\n",
-    "The following cell constructs a HuggingFace estimator using the parameters defined above. To see how the SageMaker tensor parallelism modules and functions are applied to the script, see the `train_gpt_simple.py` file."
+    "The following cell constructs a PyTorch estimator using the parameters defined above. To see how the SageMaker tensor parallelism modules and functions are applied to the script, see the `train_gpt_simple.py` file."
    ]
   },
   {