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demo.ipynb

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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Ancient Manuscript OCR Demo\n",
+    "\n",
+    "This notebook demonstrates how to use the Ancient Manuscript OCR model."
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Install dependencies\n",
+    "!pip install torch torchvision pillow huggingface_hub -q"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Download model from Hugging Face\n",
+    "from huggingface_hub import hf_hub_download\n",
+    "\n",
+    "model_path = hf_hub_download(\n",
+    "    repo_id='cosmicshubham/ancient-manuscript-ocr',\n",
+    "    filename='best_model.pth'\n",
+    ")\n",
+    "\n",
+    "print(f'Model downloaded to: {model_path}')"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "# Load and use the model\n",
+    "from inference import ManuscriptOCR\n",
+    "\n",
+    "ocr = ManuscriptOCR(model_path=model_path)\n",
+    "\n",
+    "# Predict on your image\n",
+    "text = ocr.predict('path/to/your/manuscript.jpg')\n",
+    "print(f'Recognized Text: {text}')"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 4
+}