diff --git a/.ipynb_checkpoints/run_transformer-checkpoint.ipynb b/.ipynb_checkpoints/run_transformer-checkpoint.ipynb
new file mode 100644
index 0000000..9200f10
--- /dev/null
+++ b/.ipynb_checkpoints/run_transformer-checkpoint.ipynb
@@ -0,0 +1,116 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "promotional-stage",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import torch\n",
+    "import csv\n",
+    "import lzma"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "gothic-olympus",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_train = pd.read_table('train/in.tsv', sep='\\t', header=None, quoting=3)\n",
+    "#x_train = x_train[0:200000]\n",
+    "#x_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "respiratory-train",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open('train/expected.tsv', 'r', encoding='utf8') as file:\n",
+    "    y_train = pd.read_csv(file, sep='\\t', header=None)\n",
+    "#y_train = y_train[0:200000]\n",
+    "#y_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "loving-sewing",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open('dev-0/in.tsv', 'r', encoding='utf8') as file:\n",
+    "    x_dev = pd.read_csv(file, sep='\\t', header=None)\n",
+    "#x_dev"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aware-applicant",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open('test-A/in.tsv', 'r', encoding='utf8') as file:\n",
+    "    x_test = pd.read_csv(file, sep='\\t', header=None)\n",
+    "#x_test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "lovely-density",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "https://github.com/facebookresearch/fairseq/issues/2666"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "occasional-banks",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "https://github.com/facebookresearch/fairseq/blob/main/fairseq/models/huggingface/hf_gpt2.py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "human-portal",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}
diff --git a/run.ipynb b/run.ipynb
index 9806b40..cba6075 100644
--- a/run.ipynb
+++ b/run.ipynb
@@ -3,7 +3,7 @@
   {
    "cell_type": "code",
    "execution_count": 1,
-   "id": "74100403-147c-42cd-8285-e30778c0fb66",
+   "id": "retired-freeze",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -19,7 +19,7 @@
   {
    "cell_type": "code",
    "execution_count": 2,
-   "id": "1ec57d97-a852-490e-8da4-d1e4c9676cd6",
+   "id": "colored-calculation",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -35,7 +35,7 @@
   {
    "cell_type": "code",
    "execution_count": 3,
-   "id": "86fbfb79-76e7-49f5-b722-2827f93cb03f",
+   "id": "secondary-worse",
    "metadata": {},
    "outputs": [
     {
@@ -155,7 +155,7 @@
   {
    "cell_type": "code",
    "execution_count": 4,
-   "id": "8960c975-f756-4e36-a1ce-e9fd5fdf8fe3",
+   "id": "royal-roots",
    "metadata": {},
    "outputs": [
     {
@@ -264,7 +264,7 @@
   {
    "cell_type": "code",
    "execution_count": 5,
-   "id": "6b27e6ce-e9fd-41a1-aacf-53a5fde0a7c1",
+   "id": "protective-hometown",
    "metadata": {},
    "outputs": [
     {
@@ -384,7 +384,7 @@
   {
    "cell_type": "code",
    "execution_count": 6,
-   "id": "99ae526d-9b7c-493f-be4f-f95b1c8f4b81",
+   "id": "attractive-banana",
    "metadata": {},
    "outputs": [
     {
@@ -504,7 +504,7 @@
   {
    "cell_type": "code",
    "execution_count": 7,
-   "id": "dba17668-971f-47f8-99ce-fc840b5cb74a",
+   "id": "realistic-television",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -525,7 +525,7 @@
   {
    "cell_type": "code",
    "execution_count": 8,
-   "id": "1a275c1d-75bc-4290-9332-56396d16a0f2",
+   "id": "prescription-throat",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -543,7 +543,7 @@
   {
    "cell_type": "code",
    "execution_count": 9,
-   "id": "3125d2f2-0da9-45eb-acf1-90293c6d64a3",
+   "id": "distinguished-french",
    "metadata": {},
    "outputs": [
     {
@@ -564,7 +564,7 @@
   {
    "cell_type": "code",
    "execution_count": 10,
-   "id": "031a3670-3be7-4146-97b4-0dacd4f9ae58",
+   "id": "shared-divorce",
    "metadata": {},
    "outputs": [
     {
@@ -592,7 +592,7 @@
   {
    "cell_type": "code",
    "execution_count": 15,
-   "id": "b7defd18-e281-4cf6-9941-cee560749677",
+   "id": "japanese-broad",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -618,7 +618,7 @@
   {
    "cell_type": "code",
    "execution_count": 17,
-   "id": "92c69ddd-fe58-477f-b2c2-06324a983bcc",
+   "id": "decent-initial",
    "metadata": {},
    "outputs": [
     {
@@ -657,7 +657,7 @@
   {
    "cell_type": "code",
    "execution_count": 13,
-   "id": "caff921c-d0ab-4fce-a17f-6610266b404d",
+   "id": "guilty-auditor",
    "metadata": {},
    "outputs": [
     {
@@ -680,7 +680,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "73076eb2-810f-4f85-aa3f-05ee884c413b",
+   "id": "unavailable-morrison",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -691,7 +691,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "5730562a-0200-4c8f-8f73-992fa2b36133",
+   "id": "polished-france",
    "metadata": {},
    "outputs": [],
    "source": [
@@ -701,7 +701,7 @@
   {
    "cell_type": "code",
    "execution_count": null,
-   "id": "07a09298-204c-4905-90a8-5dcb87877368",
+   "id": "underlying-lightning",
    "metadata": {},
    "outputs": [],
    "source": []
@@ -709,7 +709,7 @@
  ],
  "metadata": {
   "kernelspec": {
-   "display_name": "Python 3 (ipykernel)",
+   "display_name": "Python 3",
    "language": "python",
    "name": "python3"
   },
@@ -723,7 +723,7 @@
    "name": "python",
    "nbconvert_exporter": "python",
    "pygments_lexer": "ipython3",
-   "version": "3.9.12"
+   "version": "3.7.3"
   }
  },
  "nbformat": 4,
diff --git a/run_transformer.ipynb b/run_transformer.ipynb
new file mode 100644
index 0000000..9200f10
--- /dev/null
+++ b/run_transformer.ipynb
@@ -0,0 +1,116 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "promotional-stage",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import numpy as np\n",
+    "import pandas as pd\n",
+    "import torch\n",
+    "import csv\n",
+    "import lzma"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "gothic-olympus",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "x_train = pd.read_table('train/in.tsv', sep='\\t', header=None, quoting=3)\n",
+    "#x_train = x_train[0:200000]\n",
+    "#x_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "respiratory-train",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open('train/expected.tsv', 'r', encoding='utf8') as file:\n",
+    "    y_train = pd.read_csv(file, sep='\\t', header=None)\n",
+    "#y_train = y_train[0:200000]\n",
+    "#y_train"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "loving-sewing",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open('dev-0/in.tsv', 'r', encoding='utf8') as file:\n",
+    "    x_dev = pd.read_csv(file, sep='\\t', header=None)\n",
+    "#x_dev"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "aware-applicant",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "with open('test-A/in.tsv', 'r', encoding='utf8') as file:\n",
+    "    x_test = pd.read_csv(file, sep='\\t', header=None)\n",
+    "#x_test"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "lovely-density",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "https://github.com/facebookresearch/fairseq/issues/2666"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "occasional-banks",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "https://github.com/facebookresearch/fairseq/blob/main/fairseq/models/huggingface/hf_gpt2.py"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "human-portal",
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "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": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}