diff --git a/modules/GDS_dataset.ipynb b/modules/GDS_dataset.ipynb
index 1df019ddf..0522925b6 100644
--- a/modules/GDS_dataset.ipynb
+++ b/modules/GDS_dataset.ipynb
@@ -24,7 +24,7 @@
    "source": [
     "# GDS Integration\n",
     "\n",
-    "This notebook introduces how to integrate GDS into MONAI. It mainly include several parts as shown below.\n",
+    "This notebook introduces how to integrate GDS into MONAI. It mainly includes several parts as shown below.\n",
     "- What is GPUDirect Storage(GDS)?\n",
     "\n",
     "    GDS is the newest addition to the GPUDirect family. Like GPUDirect peer to peer (https://developer.nvidia.com/gpudirect) that enables a direct memory access (DMA) path between the memory of two graphics processing units (GPUs) and GPUDirect RDMA that enables a direct DMA path to a network interface card (NIC), GDS enables a direct DMA data path between GPU memory and storage, thus avoiding a bounce buffer through the CPU. This direct path can increase system bandwidth while decreasing latency and utilization load on the CPU and GPU.\n",
@@ -33,16 +33,20 @@
     "\n",
     "    1. GDS has been tested on following NVIDIA GPUs: T10x, T4, A10, Quadro P6000, A100, and V100. For a full list of GPUs that GDS works with, refer to the [Known Limitations](https://docs.nvidia.com/gpudirect-storage/release-notes/index.html#known-limitations) section. For more requirments, you can refer to the 3 and 4 in this [link](https://docs.nvidia.com/gpudirect-storage/release-notes/index.html#mofed-fs-req).\n",
     "\n",
-    "    2. For how to enble GDS on bare metal, you can refer to the detailed steps in this [section](https://docs.nvidia.com/dgx/dgx-os-6-user-guide/additional_software.html#installing-gpudirect-storage-support). \n",
+    "    2. To enable GDS on bare metal, follow the detailed steps provided in this [section](https://docs.nvidia.com/dgx/dgx-os-6-user-guide/additional_software.html#installing-gpudirect-storage-support). To verify successful GDS installation, run the following command:\n",
+    "        \n",
+    "        ```/usr/local/cuda-<x>.<y>/gds/tools/gdscheck.py -p``` \n",
+    "        \n",
+    "        (Replace X with the major version of the CUDA toolkit, and Y with the minor version.)\n",
     "\n",
-    "- A `GDSDataset` which inherited from `PersistantDataset`.\n",
+    "- `GDSDataset` inherited from `PersistentDataset`.\n",
     "\n",
-    "    In this tutorial, we write a `GDSDataset` is inherited from `PersistantDataset` which have rewritten the `_cachecheck` method to create and save cache using GDS.\n",
+    "    In this tutorial, we have implemented a `GDSDataset` that inherits from `PersistentDataset`. We have re-implemented the `_cachecheck` method to create and save cache using GDS.\n",
     "\n",
-    "- A simple demo to show the time comparasion from the GDS.\n",
+    "- A simple demo comparing the time taken with and without GDS.\n",
+    "\n",
+    "   In this tutorial, we are creating a conda environment to install `kvikio`, which provides a Python API for GDS. To install `kvikio` using other methods, refer to https://github.com/rapidsai/kvikio#install.\n",
     "\n",
-    "    In this tutorial, we are creating a conda environment.\n",
-    "    \n",
     "    ```conda create -n gds_env -c rapidsai-nightly -c conda-forge python=3.10 cuda-version=11.8 kvikio```"
    ]
   },