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app.ipynb

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

requirements.txt.txt

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+transformers
+torch
+#pytube