diff --git a/.gitignore b/.gitignore
index 1c18d74..cbe754f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -6,3 +6,5 @@
 *.o
 .DS_Store
 .token
+geval
+*in.tsv
\ No newline at end of file
diff --git a/notebook.ipynb b/notebook.ipynb
new file mode 100644
index 0000000..da6f02d
--- /dev/null
+++ b/notebook.ipynb
@@ -0,0 +1,163 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 11,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "unxz: challenging-america-word-gap-prediction/train/in.tsv.xz: No such file or directory\n",
+      "unxz: challenging-america-word-gap-prediction/test-A/in.tsv.xz: No such file or directory\n",
+      "unxz: challenging-america-word-gap-prediction/dev-0/in.tsv.xz: No such file or directory\n"
+     ]
+    }
+   ],
+   "source": [
+    "!unxz challenging-america-word-gap-prediction/train/in.tsv.xz --keep\n",
+    "!unxz challenging-america-word-gap-prediction/test-A/in.tsv.xz --keep\n",
+    "!unxz challenging-america-word-gap-prediction/dev-0/in.tsv.xz --keep"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "expected.tsv  in.tsv\n"
+     ]
+    }
+   ],
+   "source": [
+    "!ls challenging-america-word-gap-prediction/train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "All texts: 10\n",
+      "All labels: 10\n"
+     ]
+    }
+   ],
+   "source": [
+    "import nltk\n",
+    "def get_texts():\n",
+    "    with open(\"challenging-america-word-gap-prediction/train/in.tsv\", \"r\", encoding=\"UTF-8\") as f:\n",
+    "        i = 0\n",
+    "        while True:\n",
+    "            i+=1\n",
+    "            text = f.readline()\n",
+    "            if(text == None or i > 10):\n",
+    "                break\n",
+    "            text = text.split('\\t')[6]\n",
+    "            text = text.replace(\"-\\n\", \"\").replace(\"\\n\", \" \")\n",
+    "            yield \n",
+    "\n",
+    "# def get_words():\n",
+    "#     for text in get_texts():\n",
+    "#         for word in nltk.word_tokenize(text):\n",
+    "#             yield word\n",
+    "\n",
+    "def get_labels():\n",
+    "    with open(\"challenging-america-word-gap-prediction/train/expected.tsv\", \"r\", encoding=\"UTF-8\") as f:\n",
+    "        yield from f.readlines()[0:10]\n",
+    "\n",
+    "texts_sum = sum(1 for text in get_texts())\n",
+    "labels_sum = sum(1 for label in get_labels())\n",
+    "# words_sum = sum(1 for word in get_words())\n",
+    "print(f\"All texts: {texts_sum}\")\n",
+    "print(f\"All labels: {labels_sum}\")\n",
+    "# print(f\"All words: {words_sum}\")"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "None\n",
+      "None\n",
+      "None\n",
+      "None\n",
+      "None\n",
+      "None\n",
+      "None\n",
+      "None\n",
+      "None\n",
+      "None\n"
+     ]
+    }
+   ],
+   "source": [
+    "for text in get_texts():\n",
+    "    print(text)"
+   ]
+  },
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "## Model bigramowy odwrotny"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "class Model():\n",
+    "    def __init__(self, vocab_size, UNK_token= '<UNK>'):\n",
+    "        pass\n",
+    "    \n",
+    "    def train(corpus:list) -> None:\n",
+    "        pass\n",
+    "    \n",
+    "    def predict(text: list, probs: str) -> float:\n",
+    "        pass"
+   ]
+  }
+ ],
+ "metadata": {
+  "interpreter": {
+   "hash": "916dbcbb3f70747c44a77c7bcd40155683ae19c65e1c03b4aa3499c5328201f1"
+  },
+  "kernelspec": {
+   "display_name": "Python 3.8.5 64-bit",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.8.5"
+  },
+  "orig_nbformat": 4
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}