diff --git a/docs/docs/frigate/hardware.md b/docs/docs/frigate/hardware.md
index 0c6a8ca46..15e3b1e0a 100644
--- a/docs/docs/frigate/hardware.md
+++ b/docs/docs/frigate/hardware.md
@@ -145,7 +145,7 @@ With the [rocm](../configuration/object_detectors.md#amdrocm-gpu-detector) detec
 
 | Name            | YoloV9 Inference Time | YOLO-NAS Inference Time   |
 | --------------- | --------------------- | ------------------------- |
-| AMD 780M        | ~ 14 ms               | 320: ~ 60 ms 640: ~ 80 ms |
+| AMD 780M        | ~ 14 ms               | 320: ~ 30 ms 640: ~ 60 ms |
 
 ## Community Supported Detectors
 
diff --git a/notebooks/YOLO_NAS_Pretrained_Export.ipynb b/notebooks/YOLO_NAS_Pretrained_Export.ipynb
index 4fee19183..4e0439e9e 100644
--- a/notebooks/YOLO_NAS_Pretrained_Export.ipynb
+++ b/notebooks/YOLO_NAS_Pretrained_Export.ipynb
@@ -13,15 +13,15 @@
     },
     {
       "cell_type": "code",
-      "source": [
-        "! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.11/dist-packages/super_gradients/training/pretrained_models.py\n",
-        "! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.11/dist-packages/super_gradients/training/utils/checkpoint_utils.py"
-      ],
+      "execution_count": null,
       "metadata": {
         "id": "NiRCt917KKcL"
       },
-      "execution_count": null,
-      "outputs": []
+      "outputs": [],
+      "source": [
+        "! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.11/dist-packages/super_gradients/training/pretrained_models.py\n",
+        "! sed -i 's/sghub.deci.ai/sg-hub-nv.s3.amazonaws.com/' /usr/local/lib/python3.11/dist-packages/super_gradients/training/utils/checkpoint_utils.py"
+      ]
     },
     {
       "cell_type": "code",
@@ -51,6 +51,7 @@
         "model.export(\"yolo_nas_s.onnx\",\n",
         "             output_predictions_format=DetectionOutputFormatMode.FLAT_FORMAT,\n",
         "             max_predictions_per_image=20,\n",
+        "             num_pre_nms_predictions=300,\n",
         "             confidence_threshold=0.4,\n",
         "             input_image_shape=(320,320),\n",
         "            )"