talking.ipynb

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        "import streamlit as st\n",
        "from transformers import VitsModel, AutoTokenizer\n",
        "import torch\n",
        "import numpy as np\n",
        "import io\n",
        "import soundfile as sf"
      ]
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        "# Load model and tokenizer\n",
        "model = VitsModel.from_pretrained(\"facebook/mms-tts-eng\")\n",
        "tokenizer = AutoTokenizer.from_pretrained(\"facebook/mms-tts-eng\")\n",
        "\n",
        "def generate_speech(text):\n",
        "  inputs = tokenizer(text, return_tensors=\"pt\")\n",
        "\n",
        "  with torch.no_grad():\n",
        "    output = model(**inputs).waveform  # Corrected typo: waveform (not waveformform)\n",
        "\n",
        "  # Convert the waveform tensor to a NumPy array\n",
        "  waveform = output.squeeze().cpu().numpy()\n",
        "\n",
        "  # Convert the waveform to bytes\n",
        "  audio_bytes_io = io.BytesIO()\n",
        "  sf.write(audio_bytes_io, waveform, samplerate=22050, format='WAV')\n",
        "  audio_bytes_io.seek(0)\n",
        "\n",
        "  return audio_bytes_io\n"
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