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+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "id": "8fa27a71",
+   "metadata": {},
+   "source": [
+    "# Week 7 Exercise: Fine-Tuning Gemma 3 Open Source LLM for Price Prediction\n",
+    "\n",
+    "## Project Overview\n",
+    "Fine-tuning an open-source Large Language Model to predict product prices based on textual descriptions.\n",
+    "\n",
+    "## Base Model\n",
+    "unsloth/gemma-3-4b-it\n",
+    "\n",
+    "## Dataset\n",
+    "ed-donner/pricer-data\n",
+    "\n",
+    "## Fine Tuning Details\n",
+    "*   Fine-tuning Approach: LoRA (Low-Rank Adaptation)\n",
+    "*   Target modules: All attention and MLP layers\n",
+    "*   Framework: Unsloth + TRL (Transformer Reinforcement Learning)\n",
+    "*   Chat template formatting for consistent input structure\n",
+    "*   4-bit quantization for memory-efficient training\n",
+    "\n",
+    "link to colab notebook : https://colab.research.google.com/drive/1sCQQ_OoR2kd1ASivfbUQx-lIE-wHIT6s?usp=sharing\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "language_info": {
+   "name": "python"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}