diff --git a/advanced_training_notebook.ipynb b/advanced_training_notebook.ipynb
index 5093211..5a6a418 100644
--- a/advanced_training_notebook.ipynb
+++ b/advanced_training_notebook.ipynb
@@ -10,7 +10,6 @@
     "  <img src=\"https://raw.githubusercontent.com/MasterPhooey/MicroWakeWord-Trainer-Docker/refs/heads/main/mmw.png\" alt=\"MicroWakeWord Trainer Logo\" width=\"100\" />\n",
     "  <h1>MicroWakeWord Trainer Docker</h1>\n",
     "</div>\n",
-    "**This notebook requires 24G of Vram.**\n",
     "\n",
     "This notebook steps you through training a robust microWakeWord model. It is intended as a **starting point** for users looking to create a high-performance wake word detection model. This notebook is optimized for Python 3.10.\n",
     "\n",
@@ -641,7 +640,7 @@
     "config[\"clip_duration_ms\"] = 2000  # Increased\n",
     "\n",
     "config[\"target_minimization\"] = 0.9\n",
-    "config[\"minimization_metric\"] = None  # Updated\n",
+    "config[\"minimization_metric\"] = \"false_positive_rate\"  # Updated\n",
     "config[\"maximization_metric\"] = \"average_viable_recall\"\n",
     "\n",
     "with open(os.path.join(\"training_parameters.yaml\"), \"w\") as file:\n",
@@ -676,20 +675,20 @@
     "--training_config='training_parameters.yaml' \\\n",
     "--train 1 \\\n",
     "--restore_checkpoint 1 \\\n",
-    "--test_tf_nonstreaming 1 \\\n",
-    "--test_tflite_nonstreaming 1 \\\n",
-    "--test_tflite_nonstreaming_quantized 1 \\\n",
-    "--test_tflite_streaming 1 \\\n",
+    "--test_tf_nonstreaming 0 \\\n",
+    "--test_tflite_nonstreaming 0 \\\n",
+    "--test_tflite_nonstreaming_quantized 0 \\\n",
+    "--test_tflite_streaming 0 \\\n",
     "--test_tflite_streaming_quantized 1 \\\n",
     "--use_weights \"best_weights\" \\\n",
     "mixednet \\\n",
-    "--pointwise_filters \"64,96,128,160\" \\\n",
-    "--repeat_in_block \"2,2,3,3\" \\\n",
-    "--mixconv_kernel_sizes '[5], [7,11], [9,15], [17,23]' \\\n",
-    "--residual_connection \"1,1,1,0\" \\\n",
-    "--first_conv_filters 48 \\\n",
-    "--first_conv_kernel_size 7 \\\n",
-    "--stride 2 \n"
+    "--pointwise_filters \"64,64,64,64\" \\\n",
+    "--repeat_in_block \"1,1,1,1\" \\\n",
+    "--mixconv_kernel_sizes '[5], [7,11], [9,15], [23]' \\\n",
+    "--residual_connection \"0,0,0,0\" \\\n",
+    "--first_conv_filters 32 \\\n",
+    "--first_conv_kernel_size 5 \\\n",
+    "--stride 2\n"
    ]
   },
   {
@@ -702,7 +701,9 @@
    "source": [
     "import shutil\n",
     "import json\n",
-    "from IPython.display import FileLink, HTML\n",
+    "from http.server import HTTPServer, SimpleHTTPRequestHandler\n",
+    "import threading\n",
+    "from pathlib import Path\n",
     "\n",
     "# Copy the TFLite model file to the working directory\n",
     "source_path = \"trained_models/wakeword/tflite_stream_state_internal_quant/stream_state_internal_quant.tflite\"\n",
@@ -712,7 +713,7 @@
     "# Define the JSON metadata for the model\n",
     "json_data = {\n",
     "    \"type\": \"micro\",\n",
-    "    \"wake_word\": \"hey_norman\",  # Adjust based on your target wake word\n",
+    "    \"wake_word\": \"khum_puter\",  # Adjust based on your target wake word\n",
     "    \"author\": \"master phooey\",\n",
     "    \"website\": \"https://github.com/MasterPhooey/MicroWakeWord-Trainer-Docker\",\n",
     "    \"model\": \"stream_state_internal_quant.tflite\",\n",
@@ -732,19 +733,37 @@
     "with open(json_path, \"w\") as json_file:\n",
     "    json.dump(json_data, json_file, indent=2)\n",
     "\n",
-    "# Generate download links with styled HTML\n",
-    "tflite_link = FileLink(destination_path)\n",
-    "json_link = FileLink(json_path)\n",
+    "# Custom HTTPRequestHandler to set the Content-Disposition header\n",
+    "class CustomHTTPRequestHandler(SimpleHTTPRequestHandler):\n",
+    "    def end_headers(self):\n",
+    "        if self.path.endswith(\".json\"):\n",
+    "            self.send_header(\"Content-Disposition\", \"attachment\")\n",
+    "        super().end_headers()\n",
     "\n",
+    "# Start an HTTP server in a separate thread\n",
+    "def start_server():\n",
+    "    server = HTTPServer((\"0.0.0.0\", 8000), CustomHTTPRequestHandler)\n",
+    "    print(\"Serving files on http://localhost:8000\")\n",
+    "    server.serve_forever()\n",
+    "\n",
+    "thread = threading.Thread(target=start_server, daemon=True)\n",
+    "thread.start()\n",
+    "\n",
+    "# Generate download links with styled HTML\n",
     "html_content = f\"\"\"\n",
+    "<div align=\\\"center\\\">,\n",
+    "<img src=\\\"https://raw.githubusercontent.com/MasterPhooey/MicroWakeWord-Trainer-Docker/refs/heads/main/mmw.png\\\" alt=\\\"MicroWakeWord Trainer Logo\\\" width=\\\"100\\\" />\\n\"\n",
+    "<h1>MicroWakeWord Trainer Docker</h1>\n",
+    "</div>\\n\n",
     "<h3 style=\"color:orange;\">Your files are ready for download:</h3>\n",
     "<ul>\n",
-    "    <li><b><a href=\"{tflite_link.url}\" target=\"_blank\" style=\"color:orange;\">TFLite Model: stream_state_internal_quant.tflite</a></b></li>\n",
-    "    <li><b><a href=\"{json_link.url}\" target=\"_blank\" style=\"color:orange;\">JSON Metadata: stream_state_internal_quant.json</a></b></li>\n",
+    "    <li><b><a href=\"http://localhost:8000/stream_state_internal_quant.tflite\" target=\"_blank\" style=\"color:orange;\">TFLite Model: stream_state_internal_quant.tflite</a></b></li>\n",
+    "    <li><b><a href=\"http://localhost:8000/stream_state_internal_quant.json\" target=\"_blank\" style=\"color:orange;\">JSON Metadata: stream_state_internal_quant.json</a></b></li>\n",
     "</ul>\n",
     "<p style=\"font-size:12px; color:gray;\">Click the links to download the files. Ensure the files are moved to the correct directory for deployment.</p>\n",
     "\"\"\"\n",
     "\n",
+    "from IPython.display import HTML\n",
     "display(HTML(html_content))"
    ]
   }