update description

Author: dnth

examples/analyzing-labelbox-datasets.ipynb

@@ -45,16 +45,7 @@
     "[![Explore the Docs](https://img.shields.io/badge/Explore%20the%20Docs-blue?style=for-the-badge&labelColor=gray&logo=read-the-docs)](https://visual-layer.readme.io/docs/run-on-precomputed-feature-vectors)\n",
     "\n",
     "\n",
-    "If you have datasets from LabelBox this notebook shows how you can analyze them.\n",
-    "```"
-   ]
-  },
-  {
-   "cell_type": "markdown",
-   "id": "bae6d61b-3beb-46ad-b53a-895e78d3cf5f",
-   "metadata": {},
-   "source": [
-    "In this notebook we show an end-to-end example on how you can pre-compute feature vectors using fastdup and DINOv2 model and use the features to surface dataset issues."
+    "If you have datasets from LabelBox this notebook shows how you can download datasets from your Labelbox account and analyze them for issues with fastdup."
    ]
   },
   {
@@ -179,7 +170,8 @@
    "id": "390f9cd9-08cf-42bb-947b-546f7a520e5b",
    "metadata": {},
    "source": [
-    "## Download Dataset "
+    "## Download Dataset\n",
+    "The Labelbox SDK does not provide a way to bulk download the dataset. We will download the dataset by iterating over each image in the dataset."
    ]
   },
   {
@@ -230,7 +222,8 @@
    "id": "1766b743-51bc-4be6-8827-5777fa085a93",
    "metadata": {},
    "source": [
-    "## Run fastdup"
+    "## Run fastdup\n",
+    "One the dataset download completes, analyze the image folder where the dataset is stored."
    ]
   },
   {
@@ -1452,7 +1445,7 @@
    "metadata": {},
    "source": [
     "## Wrap Up\n",
-    "In this tutorial, we showed how you can run fastdup using pre-computed feature vectors. Running over pre-computed feature vectors significantly reduces run time compared to running over raw image files.\n",
+    "In this tutorial, we showed how you can download datasets from your Labelbox and analyze it with fastdup.\n",
     "\n",
     "Next, feel free to check out other tutorials -\n",
     "\n",