Add example for how to use.

README.md

@@ -19,6 +19,29 @@ arxiv link: https://arxiv.org/abs/1811.00671
 
 Abstract: Consistency is a long standing issue faced by dialogue models. In this paper, we frame the consistency of dialogue agents as natural language inference (NLI) and create a new natural language inference dataset called Dialogue NLI. We propose a method which demonstrates that a model trained on Dialogue NLI can be used to improve the consistency of a dialogue model, and evaluate the method with human evaluation and with automatic metrics on a suite of evaluation sets designed to measure a dialogue model’s consistency.
 
+## How to use
+
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset('xksteven/dialogue_nli', split='train')
+```
+
+label candidates:
+  - entailment
+  - contradiction
+  - neutral
+
+Train dataset features.
+```
+Dataset({
+    features: ['id', 'label', 'premise', 'hypothesis', 'dtype'],
+    num_rows: 310110
+})
+```
+
+
 ### Citation
 
 ```