diff --git a/clone_voice.ipynb b/clone_voice.ipynb
index 5fab639..a5e3391 100644
--- a/clone_voice.ipynb
+++ b/clone_voice.ipynb
@@ -9,10 +9,13 @@
     "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)"
+    "model = load_codec_model(use_gpu=True)\n",
+    "tokenizer = BertTokenizer.from_pretrained(\"bert-base-multilingual-cased\")"
    ]
   },
   {
@@ -59,7 +62,7 @@
     "# get seconds of audio\n",
     "seconds = wav.shape[-1] / model.sample_rate\n",
     "# generate semantic tokens\n",
-    "semantic_tokens = generate_text_semantic(text, max_gen_duration_s=seconds)"
+    "semantic_tokens = generate_text_semantic(text, max_gen_duration_s=seconds, top_k=50, top_p=.95, temp=0.7)"
    ]
   },
   {
@@ -117,12 +120,49 @@
    "source": [
     "from bark.api import generate_audio\n",
     "from bark.generation import SAMPLE_RATE\n",
-    "text_prompt = \"\"\"\n",
-    "    Hello, my name is Suno. And, uh — and I like pizza. [laughs] \n",
-    "    But I also have other interests such as playing tic tac toe.\n",
-    "\"\"\"\n",
-    "voice_name = \"speaker_0\" # use your custom voice name here if you have one\n",
-    "audio_array = generate_audio(text_prompt, history_prompt=voice_name)"
+    "text_prompt = \"Hello, my name is Suno. And, uh — and I like pizza. [laughs]\"\n",
+    "voice_name = \"speaker_0\" # use your custom voice name here if you have one"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# simple generation\n",
+    "audio_array = generate_audio(text_prompt, history_prompt=voice_name, text_temp=0.7, waveform_temp=0.7)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# generation with more control\n",
+    "from bark.generation import codec_decode, generate_coarse, generate_fine, generate_text_semantic\n",
+    "x_semantic = generate_text_semantic(\n",
+    "    text_prompt,\n",
+    "    history_prompt=voice_name,\n",
+    "    temp=0.7,\n",
+    "    top_k=50,\n",
+    "    top_p=0.95,\n",
+    ")\n",
+    "\n",
+    "x_coarse_gen = generate_coarse(\n",
+    "    x_semantic,\n",
+    "    history_prompt=voice_name,\n",
+    "    temp=0.7,\n",
+    "    top_k=50,\n",
+    "    top_p=0.95,\n",
+    ")\n",
+    "x_fine_gen = generate_fine(\n",
+    "    x_coarse_gen,\n",
+    "    history_prompt=voice_name,\n",
+    "    temp=0.5,\n",
+    ")\n",
+    "audio_array = codec_decode(x_fine_gen)"
    ]
   },
   {
diff --git a/generate.ipynb b/generate.ipynb
index 115506b..4f2bb89 100644
--- a/generate.ipynb
+++ b/generate.ipynb
@@ -8,12 +8,49 @@
    "source": [
     "from bark.api import generate_audio\n",
     "from bark.generation import SAMPLE_RATE\n",
-    "text_prompt = \"\"\"\n",
-    "    Hello, my name is Suno. And, uh — and I like pizza. [laughs] \n",
-    "    But I also have other interests such as playing tic tac toe.\n",
-    "\"\"\"\n",
-    "voice_name = \"speaker_0\" # use your custom voice name here if you have one\n",
-    "audio_array = generate_audio(text_prompt, history_prompt=voice_name)"
+    "text_prompt = \"Hello, my name is Suno. And, uh — and I like pizza. [laughs]\"\n",
+    "voice_name = \"speaker_0\" # use your custom voice name here if you have one"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# simple generation\n",
+    "audio_array = generate_audio(text_prompt, history_prompt=voice_name, text_temp=0.7, waveform_temp=0.7)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# generation with more control\n",
+    "from bark.generation import codec_decode, generate_coarse, generate_fine, generate_text_semantic\n",
+    "x_semantic = generate_text_semantic(\n",
+    "    text_prompt,\n",
+    "    history_prompt=voice_name,\n",
+    "    temp=0.7,\n",
+    "    top_k=50,\n",
+    "    top_p=0.95,\n",
+    ")\n",
+    "\n",
+    "x_coarse_gen = generate_coarse(\n",
+    "    x_semantic,\n",
+    "    history_prompt=voice_name,\n",
+    "    temp=0.7,\n",
+    "    top_k=50,\n",
+    "    top_p=0.95,\n",
+    ")\n",
+    "x_fine_gen = generate_fine(\n",
+    "    x_coarse_gen,\n",
+    "    history_prompt=voice_name,\n",
+    "    temp=0.5,\n",
+    ")\n",
+    "audio_array = codec_decode(x_fine_gen)"
    ]
   },
   {