--- a
+++ b/Prediction.ipynb
@@ -0,0 +1,121 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "100%|██████████| 1/1 [00:00<00:00, 14.85it/s]\n"
+     ]
+    },
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Prediting SIF Stability...\n",
+      "Prediting SGF Stability...\n",
+      "Predicted SIF/SGF stability saved to the original file:  Sample_Sequence.csv\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Compound</th>\n",
+       "      <th>SMILES</th>\n",
+       "      <th>Stability_in_SIF</th>\n",
+       "      <th>Stability_in_SGF</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>Oxytocin</td>\n",
+       "      <td>CC[C@H](C)[C@H]1C(=O)N[C@H](C(=O)N[C@H](C(=O)N...</td>\n",
+       "      <td>Not Stable</td>\n",
+       "      <td>Stable</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "   Compound                                             SMILES  \\\n",
+       "0  Oxytocin  CC[C@H](C)[C@H]1C(=O)N[C@H](C(=O)N[C@H](C(=O)N...   \n",
+       "\n",
+       "  Stability_in_SIF Stability_in_SGF  \n",
+       "0       Not Stable           Stable  "
+      ]
+     },
+     "execution_count": 1,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "from lib.pred_util import model_predict, pep_feat, save_results\n",
+    "\n",
+    "#Define the path to the file that includes peptide sequence\n",
+    "Peptide_Path = 'Sample_Sequence.csv'\n",
+    "\n",
+    "#Featurising Peptides\n",
+    "peptide_features= pep_feat(Peptide_Path)\n",
+    "\n",
+    "#Make Predictions \n",
+    "SIF_Stability = model_predict(feat=peptide_features,Env='SIF')\n",
+    "SGF_Stability = model_predict(feat=peptide_features,Env='SGF')\n",
+    "\n",
+    "#Save Results\n",
+    "save_results(Peptide_Path,SIF_Stability,SGF_Stability)\n"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3.7.7 ('PolyML')",
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+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
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+}