diff --git a/clone_voice.ipynb b/clone_voice.ipynb
index c25f7e3..7c687bc 100644
--- a/clone_voice.ipynb
+++ b/clone_voice.ipynb
@@ -9,13 +9,10 @@
     "from bark.generation import load_codec_model, generate_text_semantic\n",
     "from encodec.utils import convert_audio\n",
     "\n",
-    "from transformers import BertTokenizer\n",
-    "\n",
     "import torchaudio\n",
     "import torch\n",
     "\n",
-    "model = load_codec_model(use_gpu=True)\n",
-    "tokenizer = BertTokenizer.from_pretrained(\"bert-base-multilingual-cased\")"
+    "model = load_codec_model(use_gpu=True)"
    ]
   },
   {
@@ -119,9 +116,15 @@
    "outputs": [],
    "source": [
     "from bark.api import generate_audio\n",
+    "from transformers import BertTokenizer\n",
     "from bark.generation import SAMPLE_RATE, preload_models, codec_decode, generate_coarse, generate_fine, generate_text_semantic\n",
+    "\n",
+    "# Enter your prompt and speaker here\n",
     "text_prompt = \"Hello, my name is Serpy. And, uh — and I like pizza. [laughs]\"\n",
-    "voice_name = \"speaker_0\" # use your custom voice name here if you have one"
+    "voice_name = \"speaker_0\" # use your custom voice name here if you have one\n",
+    "\n",
+    "# load the tokenizer\n",
+    "tokenizer = BertTokenizer.from_pretrained(\"bert-base-multilingual-cased\")"
    ]
   },
   {
diff --git a/generate.ipynb b/generate.ipynb
index e124459..174d7f8 100644
--- a/generate.ipynb
+++ b/generate.ipynb
@@ -7,9 +7,15 @@
    "outputs": [],
    "source": [
     "from bark.api import generate_audio\n",
+    "from transformers import BertTokenizer\n",
     "from bark.generation import SAMPLE_RATE, preload_models, codec_decode, generate_coarse, generate_fine, generate_text_semantic\n",
+    "\n",
+    "# Enter your prompt and speaker here\n",
     "text_prompt = \"Hello, my name is Serpy. And, uh — and I like pizza. [laughs]\"\n",
-    "voice_name = \"speaker_0\" # use your custom voice name here if you have one"
+    "voice_name = \"speaker_0\" # use your custom voice name here if you have one\n",
+    "\n",
+    "# load the tokenizer\n",
+    "tokenizer = BertTokenizer.from_pretrained(\"bert-base-multilingual-cased\")"
    ]
   },
   {