Add runnable Colab notebook

lahgtna_colab.ipynb

@@ -0,0 +1,131 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# 🗣️ Lahgtna — Egyptian-Arabic TTS on Colab\n",
+    "\n",
+    "Run the **v3** model on a free Colab GPU.\n",
+    "**First: Runtime → Change runtime type → T4 GPU.**"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "!pip install -q omnivoice catt-tashkeel num2words soundfile"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Log in to Hugging Face (private repo — use a READ token)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "from huggingface_hub import login\n",
+    "login()"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Load model + reference voice"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "import torch\n",
+    "from omnivoice.models.omnivoice import OmniVoice\n",
+    "from huggingface_hub import hf_hub_download\n",
+    "\n",
+    "REPO = \"ehabnegm/lahgtna-omnivoice-egyptian-v3\"\n",
+    "model = OmniVoice.from_pretrained(REPO, device_map=\"cuda\", dtype=torch.float16)\n",
+    "ref_audio = hf_hub_download(REPO, \"reference.wav\")\n",
+    "ref_text  = \"كان العمل التطوعي واللي لما تفتح الباب بس ليه الناس\""
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Text front-end + long-form helper (chunk → no drift)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "import re, numpy as np, soundfile as sf\n",
+    "from num2words import num2words\n",
+    "_DIGITS = str.maketrans(\"٠١٢٣٤٥٦٧٨٩\", \"0123456789\")\n",
+    "HARAKAT = re.compile(r\"[ً-ْٰـ]\")\n",
+    "def prep(t):\n",
+    "    t = t.translate(_DIGITS)\n",
+    "    t = re.sub(r\"\\d+\", lambda m: \" \" + num2words(int(m.group()), lang=\"ar\") + \" \", t)\n",
+    "    t = re.sub(r\"[A-Za-z]+\", \" \", t)\n",
+    "    t = HARAKAT.sub(\"\", t).replace(\"ى\", \"ي\")\n",
+    "    return re.sub(r\"\\s+\", \" \", t).strip()\n",
+    "def chunks(t):\n",
+    "    out, cur = [], \"\"\n",
+    "    for p in re.split(r\"([،؛\\.؟!\\n]+)\", t):\n",
+    "        cur += p\n",
+    "        if re.search(r\"[،؛\\.؟!\\n]\", p):\n",
+    "            if cur.strip(): out.append(cur.strip())\n",
+    "            cur = \"\"\n",
+    "    if cur.strip(): out.append(cur.strip())\n",
+    "    return out or [t]\n",
+    "def synth(text, num_step=16):\n",
+    "    parts = [model.generate(text=prep(c), language=\"arz\", ref_audio=ref_audio, ref_text=ref_text, num_step=num_step)[0] for c in chunks(text) if prep(c)]\n",
+    "    return np.concatenate(parts)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "### Generate & play"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "metadata": {},
+   "execution_count": null,
+   "outputs": [],
+   "source": [
+    "from IPython.display import Audio\n",
+    "text = \"أهلاً بحضرتك، معاك المساعد الذكي. اتفضل قوللي محتاج إيه؟\"\n",
+    "sf.write(\"out.wav\", synth(text), 24000)\n",
+    "Audio(\"out.wav\")"
+   ]
+  }
+ ],
+ "metadata": {
+  "accelerator": "GPU",
+  "colab": {
+   "provenance": []
+  },
+  "kernelspec": {
+   "name": "python3",
+   "display_name": "Python 3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 0
+}