{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "ename": "ModuleNotFoundError",
     "evalue": "No module named 'bark'",
     "output_type": "error",
     "traceback": [
      "\u001b[0;31m---------------------------------------------------------------------------\u001b[0m",
      "\u001b[0;31mModuleNotFoundError\u001b[0m                       Traceback (most recent call last)",
      "Cell \u001b[0;32mIn[1], line 10\u001b[0m\n\u001b[1;32m      7\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mnltk\u001b[39;00m  \u001b[39m# we'll use this to split into sentences\u001b[39;00m\n\u001b[1;32m      8\u001b[0m \u001b[39mimport\u001b[39;00m \u001b[39mnumpy\u001b[39;00m \u001b[39mas\u001b[39;00m \u001b[39mnp\u001b[39;00m\n\u001b[0;32m---> 10\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mbark\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mgeneration\u001b[39;00m \u001b[39mimport\u001b[39;00m (\n\u001b[1;32m     11\u001b[0m     generate_text_semantic,\n\u001b[1;32m     12\u001b[0m     preload_models,\n\u001b[1;32m     13\u001b[0m )\n\u001b[1;32m     14\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mbark\u001b[39;00m\u001b[39m.\u001b[39;00m\u001b[39mapi\u001b[39;00m \u001b[39mimport\u001b[39;00m semantic_to_waveform\n\u001b[1;32m     15\u001b[0m \u001b[39mfrom\u001b[39;00m \u001b[39mbark\u001b[39;00m \u001b[39mimport\u001b[39;00m generate_audio, SAMPLE_RATE\n",
      "\u001b[0;31mModuleNotFoundError\u001b[0m: No module named 'bark'"
     ]
    }
   ],
   "source": [
    "import os\n",
    "\n",
    "os.environ[\"CUDA_VISIBLE_DEVICES\"] = \"0\"\n",
    "\n",
    "\n",
    "from IPython.display import Audio\n",
    "import nltk  # we'll use this to split into sentences\n",
    "import numpy as np\n",
    "\n",
    "from bark.generation import (\n",
    "    generate_text_semantic,\n",
    "    preload_models,\n",
    ")\n",
    "from bark.api import semantic_to_waveform\n",
    "from bark import generate_audio, SAMPLE_RATE"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "preload_models()"
   ]
  }
 ],
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