From a8054e64a2c1913e3ea859a61e8b53fe4be41b26 Mon Sep 17 00:00:00 2001
From: Marcin Kardas <mkardas@fb.com>
Date: Thu, 7 May 2020 15:51:18 +0100
Subject: [PATCH] Update README

---
 README.md                                     |  8 +++--
 notebooks/training/lm.ipynb                   | 34 +++++++++++++++++++
 notebooks/training/table-segmentation.ipynb   | 34 +++++++++++++++++++
 .../training/table-type-classifier.ipynb      | 34 +++++++++++++++++++
 4 files changed, 107 insertions(+), 3 deletions(-)
 create mode 100644 notebooks/training/lm.ipynb
 create mode 100644 notebooks/training/table-segmentation.ipynb
 create mode 100644 notebooks/training/table-type-classifier.ipynb

diff --git a/README.md b/README.md
index c54e8d6..607ec65 100644
--- a/README.md
+++ b/README.md
@@ -23,14 +23,16 @@ We publish the following datasets:
 * [PWCLeaderboards](https://github.com/paperswithcode/axcell/releases/download/v1.0/pwc-leaderboards.json.xz)
 
 See [datasets](notebooks/datasets.ipynb) notebook for an example of how to load the datasets provided below. The [extraction](notebooks/extraction.ipynb) notebook shows how to use `axcell` to extract text and tables from papers.
-## Training
-
-
 
 ## Evaluation
 
 See the [evaluation](notebooks/evaluation.ipynb) notebook for the full example on how to evaluate AxCell on the PWCLeaderboards dataset. 
 
+## Training
+
+* [pre-training language model](notebooks/training/lm.ipynb) on the ArxivPapers dataset 
+* [table type classifier](notebooks/training/table-type-classifier.ipynb) and [table segmentation](notebooks/training/table-segmentation.ipynb) on the SegmentedResults dataset 
+
 ## Pre-trained Models
 
 You can download pretrained models here:
diff --git a/notebooks/training/lm.ipynb b/notebooks/training/lm.ipynb
new file mode 100644
index 0000000..e9c9d18
--- /dev/null
+++ b/notebooks/training/lm.ipynb
@@ -0,0 +1,34 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Language Model Pre-training\n",
+    "\n",
+    "Coming soon"
+   ]
+  }
+ ],
+ "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": "3.6.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/notebooks/training/table-segmentation.ipynb b/notebooks/training/table-segmentation.ipynb
new file mode 100644
index 0000000..f6aa91f
--- /dev/null
+++ b/notebooks/training/table-segmentation.ipynb
@@ -0,0 +1,34 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Table Segmentation Training\n",
+    "\n",
+    "Coming soon"
+   ]
+  }
+ ],
+ "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": "3.6.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}
diff --git a/notebooks/training/table-type-classifier.ipynb b/notebooks/training/table-type-classifier.ipynb
new file mode 100644
index 0000000..a7471bc
--- /dev/null
+++ b/notebooks/training/table-type-classifier.ipynb
@@ -0,0 +1,34 @@
+{
+ "cells": [
+  {
+   "cell_type": "markdown",
+   "metadata": {},
+   "source": [
+    "# Table Type Classifier Training \n",
+    "\n",
+    "Coming soon"
+   ]
+  }
+ ],
+ "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": "3.6.8"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}