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app.ipynb
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{
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"nbformat": 4,
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"nbformat_minor": 0,
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"metadata": {
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"colab": {
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"provenance": []
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},
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"kernelspec": {
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"name": "python3",
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"display_name": "Python 3"
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},
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"language_info": {
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"name": "python"
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}
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},
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"cells": [
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{
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"cell_type": "code",
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"execution_count": null,
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"metadata": {
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"id": "o2EjqHT7vvJv"
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},
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"outputs": [],
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"source": [
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"from transformers import pipeline\n",
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"import gradio as gr\n",
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"\n",
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"pipe = pipeline(model=\"Yasaman/whisper_fa\")\n",
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"\n",
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"def transcribe(audio):\n",
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" text = pipe(audio)[\"text\"]\n",
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" return text\n",
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"\n",
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"iface = gr.Interface(\n",
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" fn=transcribe, \n",
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" inputs=gr.Audio(source=\"microphone\", type=\"filepath\"), \n",
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" outputs=\"text\",\n",
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" title=\"Whisper Small Persian\",\n",
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" description=\"Realtime demo for Persian speech recognition using a fine-tuned Whisper small model.\",\n",
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")\n",
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"\n",
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"iface.launch()"
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]
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}
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]
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}
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