diff --git a/notebooks/piper_multilingual_training_notebook.ipynb b/notebooks/piper_multilingual_training_notebook.ipynb
index cb96aac..a6b6864 100644
--- a/notebooks/piper_multilingual_training_notebook.ipynb
+++ b/notebooks/piper_multilingual_training_notebook.ipynb
@@ -4,7 +4,8 @@
   "metadata": {
     "colab": {
       "provenance": [],
-      "authorship_tag": "ABX9TyPovMyxp8xorYRHeQp1RAP2",
+      "gpuType": "T4",
+      "authorship_tag": "ABX9TyOhGmWaOcJ8eRFW1QnG2XyK",
       "include_colab_link": true
     },
     "kernelspec": {
@@ -13,7 +14,9 @@
     },
     "language_info": {
       "name": "python"
-    }
+    },
+    "accelerator": "GPU",
+    "gpuClass": "standard"
   },
   "cells": [
     {
@@ -140,7 +143,7 @@
         "%cd /content/dataset\n",
         "!mkdir /content/dataset/wavs\n",
         "#@markdown ### Audio dataset path to unzip\n",
-        "zip_path = \"/content/drive/MyDrive/Fakeyou/odal_castilian/wavs16k.zip\" #@param {type:\"string\"}\n",
+        "zip_path = \"/content/drive/MyDrive/Fakeyou/aldEnhanced/wavs.zip\" #@param {type:\"string\"}\n",
         "!unzip \"{zip_path}\" -d /content/dataset/wavs\n",
         "#@markdown ---"
       ],
@@ -221,7 +224,7 @@
         "dataset_format = \"ljspeech\" #@param [\"ljspeech\", \"mycroft\"]\n",
         "#@markdown ---\n",
         "#@markdown ### Select the sample rate of the dataset\n",
-        "sample_rate = \"16000\" #@param [\"16000\", \"22050\"]\n",
+        "sample_rate = \"22050\" #@param [\"16000\", \"22050\"]\n",
         "#@markdown ---\n",
         "%cd /content/piper/src/python\n",
         "!python -m piper_train.preprocess \\\n",
@@ -252,17 +255,17 @@
         "if finetune:\n",
         "    ft_command = '--resume_from_checkpoint \"/content/pretrained.ckpt\" '\n",
         "    try:\n",
-        "        with open('/CONTENT/PIPER/NOTEBOOKS/pretrained_models.json') as f:\n",
+        "        with open('/content/piper/notebooks/pretrained_models.json') as f:\n",
         "            pretrained_models = json.load(f)\n",
         "        if final_language in pretrained_models:\n",
         "            models = pretrained_models[final_language]\n",
-        "            model_options = [(model_name, model_url) for model_name, model_url in models.items()]\n",
+        "            model_options = [(model_name, model_name) for model_name, model_url in models.items()]\n",
         "            model_dropdown = widgets.Dropdown(description = \"Choose pretrained model\", options=model_options)\n",
         "            download_button = widgets.Button(description=\"Download\")\n",
         "            def download_model(btn):\n",
-        "                model_name, model_url = model_dropdown.value\n",
-        "                file_id = model_url.split('/')[-2]\n",
-        "                !gdown {file_id} -O \"/content/pretrained.ckpt\"\n",
+        "                model_name = model_dropdown.value\n",
+        "                model_url = pretrained_models[final_language][model_name]\n",
+        "                !gdown \"{model_url}\" -O \"/content/pretrained.ckpt\"\n",
         "\n",
         "            download_button.on_click(download_model)\n",
         "            display(model_dropdown, download_button)\n",
@@ -273,7 +276,7 @@
         "else:\n",
         "    ft_command = \"\"\n",
         "#@makrdown ### Choose batch size based on this dataset\n",
-        "batch_size = 8 #@param {type:\"integer\"}\n",
+        "batch_size = 16 #@param {type:\"integer\"}\n",
         "#@markdown ---\n",
         "#@markdown ### Validation split\n",
         "validation_split = 0.03 #@param {type:\"number\"}\n",
@@ -284,13 +287,13 @@
         "#@markdown * low - 16Khz audio, 15-20M params\n",
         "#@markdown * medium - 22.05Khz audio, 15-20 params\n",
         "#@markdown * high - 22.05Khz audio, 28-32M params\n",
-        "quality = \"x-low\" #@param [\"high\", \"low\", \"medium\", \"x-low\"]\n",
+        "quality = \"x-low\" #@param [\"high\", \"x-low\", \"medium\"]\n",
         "#@markdown ---\n",
         "#@markdown ### For how many steps to save training checkpoints?\n",
         "checkpoint_epochs = 25 #@param {type:\"integer\"}\n",
         "#@markdown ---\n",
         "#@markdown ### Step interval to generate model samples\n",
-        "log_every_n_steps = 1000 #@param {type:\"integer\"}\n",
+        "log_every_n_steps = 250 #@param {type:\"integer\"}\n",
         "#@markdown ---\n",
         "#@markdown ### training epochs\n",
         "max_epochs = 5000 #@param {type:\"integer\"}\n",
@@ -336,11 +339,10 @@
         "    --num_sanity_val_steps 1000 \\\n",
         "    --log_every_n_steps {log_every_n_steps} \\\n",
         "    --max_epochs {max_epochs} \\\n",
-        "    {ft-command}\\\n",
+        "    {ft_command}\\\n",
         "    --precision 32"
       ],
       "metadata": {
-        "cellView": "form",
         "id": "X4zbSjXg2J3N"
       },
       "execution_count": null,