{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "Fetching 5 files: 100%|██████████| 5/5 [00:00<00:00, 76818.75it/s]\n",
      "  0%|          | 0/50 [01:05<?, ?it/s]\n"
     ]
    },
    {
     "data": {
      "text/html": [
       "\n",
       "                <audio  controls=\"controls\" >\n",
       "                    <source src=\"data:audio/wav;base64,[encoded data, 2352060 characters]\" type=\"audio/wav\" />\n",
       "                    Your browser does not support the audio element.\n",
       "                </audio>\n",
       "              "
      ],
      "text/plain": [
       "<IPython.lib.display.Audio object>"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import torchaudio\n",
    "from tangoflux import TangoFluxInference\n",
    "from IPython.display import Audio\n",
    "\n",
    "model = TangoFluxInference(name=\"declare-lab/TangoFlux\")\n",
    "\n",
    "\n",
    "audio = model.generate(\"Hammer slowly hitting the wooden table\", steps=50, duration=10)\n",
    "\n",
    "Audio(data=audio, rate=44100)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 16,
   "metadata": {},
   "outputs": [],
   "source": [
    "torchaudio.save(\"temp.wav\", audio, sample_rate=44100)"
   ]
  }
 ],
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   "display_name": "flux",
   "language": "python",
   "name": "python3"
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    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.12.8"
  }
 },
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 "nbformat_minor": 2
}
