diff --git a/email generator.ipynb b/email generator.ipynb
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+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "id": "609b9e9d-7f2b-49c3-b08f-97e6e5259242",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdin",
+     "output_type": "stream",
+     "text": [
+      "Enter the professor's name:  Ali Asadpour\n",
+      "Enter your research topic:  AI in architecture\n",
+      "Enter your name:  Masih Moafi\n"
+     ]
+    },
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\Josep\\anaconda3\\envs\\myenv\\lib\\site-packages\\transformers\\generation\\configuration_utils.py:492: UserWarning: `do_sample` is set to `False`. However, `temperature` is set to `0.7` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `temperature`.\n",
+      "  warnings.warn(\n",
+      "C:\\Users\\Josep\\anaconda3\\envs\\myenv\\lib\\site-packages\\transformers\\generation\\configuration_utils.py:497: UserWarning: `do_sample` is set to `False`. However, `top_p` is set to `0.9` -- this flag is only used in sample-based generation modes. You should set `do_sample=True` or unset `top_p`.\n",
+      "  warnings.warn(\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "\n",
+      "Generated Email:\n",
+      "\n",
+      "Dear Professor Ali Asadpour,\n",
+      "\n",
+      "    I am writing to express my interest in pursuing research under your guidance. My research topic revolves around AI in architecture.\n",
+      "\n",
+      "    I believe that your work in this area is groundbreaking, and I am eager to contribute to your ongoing projects.\n",
+      "\n",
+      "    Best regards,\n",
+      "    Masih Moafi\n",
+      "    _________________________________________\n"
+     ]
+    }
+   ],
+   "source": [
+    "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
+    "\n",
+    "# Load the tokenizer and model for GPT-J\n",
+    "tokenizer = AutoTokenizer.from_pretrained(\"EleutherAI/gpt-j-6B\")\n",
+    "model = AutoModelForCausalLM.from_pretrained(\"EleutherAI/gpt-j-6B\")\n",
+    "\n",
+    "def generate_email(professor_name, research_topic, user_name):\n",
+    "    \"\"\"\n",
+    "    Generate a professional and customizable email using GPT-J.\n",
+    "    Args:\n",
+    "        professor_name (str): The professor's name.\n",
+    "        research_topic (str): The user's research topic.\n",
+    "        user_name (str): The user's name.\n",
+    "    Returns:\n",
+    "        str: The generated email text.\n",
+    "    \"\"\"\n",
+    "    # Email template\n",
+    "    prompt = f\"\"\"\n",
+    "    Dear Professor {professor_name},\n",
+    "\n",
+    "    I am writing to express my interest in pursuing research under your guidance. My research topic revolves around {research_topic}.\n",
+    "\n",
+    "    I believe that your work in this area is groundbreaking, and I am eager to contribute to your ongoing projects.\n",
+    "\n",
+    "    Best regards,\n",
+    "    {user_name}\n",
+    "    \"\"\"\n",
+    "\n",
+    "    # Encode input\n",
+    "    input_ids = tokenizer.encode(prompt, return_tensors=\"pt\")\n",
+    "\n",
+    "    # Generate email with controlled randomness\n",
+    "    output = model.generate(\n",
+    "        input_ids,\n",
+    "        max_length=len(input_ids[0]) + 100,  # Slightly extend length to avoid truncation\n",
+    "        do_sample=False,  # Disable sampling for deterministic output\n",
+    "        temperature=0.7,  # Control output randomness\n",
+    "        top_p=0.9,  # Use nucleus sampling for coherent generation\n",
+    "        pad_token_id=tokenizer.eos_token_id  # Prevent padding issues\n",
+    "    )\n",
+    "\n",
+    "    # Decode and return the text\n",
+    "    generated_email = tokenizer.decode(output[0], skip_special_tokens=True)\n",
+    "    return generated_email.strip()\n",
+    "\n",
+    "# Input data\n",
+    "professor_name = input(\"Enter the professor's name: \")\n",
+    "research_topic = input(\"Enter your research topic: \")\n",
+    "user_name = input(\"Enter your name: \")\n",
+    "\n",
+    "# Generate and print the email\n",
+    "email = generate_email(professor_name, research_topic, user_name)\n",
+    "print(\"\\nGenerated Email:\\n\")\n",
+    "print(email)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "f575bf56-5146-49df-803a-f1ceecdbc963",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
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+   "display_name": "Python 3 (ipykernel)",
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+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
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+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
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+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
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+ "nbformat": 4,
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+}