update badge

Author: dnth

examples/feature_vectors.ipynb

@@ -45,7 +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 pre-computed feature vectors using fastdup or any other methods, you can input the features directly into fastdup to analyze for issues. Runing fastdup on feature vectors instead of raw images decreases run time significantly.\n",
+    "If you have pre-computed feature vectors using fastdup or any other methods, you can input the features directly into fastdup to analyze for issues. Running fastdup on feature vectors instead of raw images decreases run time significantly.\n",
     "\n",
     "The following code snippet shows how to run with your own feature stored in a `numpy` matrix, along with a list of the matching filenames.\n",
     "\n",
@@ -152,6 +152,14 @@
     "!tar xf images.tar.gz"
    ]
   },
+  {
+   "cell_type": "markdown",
+   "id": "a570f83f-208d-4ebf-96ce-01b99d1fa307",
+   "metadata": {},
+   "source": [
+    "Now, let's run fastdup with `dinov2s` as the `model_path`."
+   ]
+  },
   {
    "cell_type": "code",
    "execution_count": 6,
@@ -268,7 +276,7 @@
     "\n",
     "The feature vectors are stored locally in the `dinov2_feature_vectors/atrain_features.dat` file.\n",
     "\n",
-    "Let's load them with:"
+    "You can load them with:"
    ]
   },
   {