Update README.md

README.md

@@ -38,6 +38,7 @@ task_ids:
 - tabular-multi-label-classification
 ---
 
+
 # Dataset Card for "AdapTable-full" - Dataset of Few-shot Tasks from Tables
 
 ## Table of Contents
@@ -110,6 +111,7 @@ There are several dataset versions available:
     *  [AdapTable-wiki.openmoko.org](https://huggingface.co/datasets/MicPie/adaptable_wiki.openmoko.org)
     * [AdapTable-wkdu.org](https://huggingface.co/datasets/MicPie/adaptable_wkdu.org)
 
+
 * AdapTable data subsets based on clustering (for the clustering details please see our publication):
     * [AdapTable-cluster00](https://huggingface.co/datasets/MicPie/adaptable_cluster00)
     * [AdapTable-cluster01](https://huggingface.co/datasets/MicPie/adaptable_cluster01)
@@ -143,6 +145,8 @@ There are several dataset versions available:
     * [AdapTable-cluster29](https://huggingface.co/datasets/MicPie/adaptable_cluster29)
     * [AdapTable-cluster-noise](https://huggingface.co/datasets/MicPie/adaptable_cluster-noise)
 
+
+
 ### Supported Tasks and Leaderboards
 
 Since the tables come from the web, the distribution of tasks and topics is very broad. The shape of our dataset is very wide, i.e., we have 1000's of tasks, while each task has only a few examples, compared to most current NLP datasets which are very deep, i.e., 10s of tasks with many examples. This implies that our dataset covers a broad range of potential tasks, e.g., multiple-choice, question-answering, table-question-answering, text-classification, etc.