Update README.md

README.md

@@ -1,3 +1,7 @@
+## Hebrew Conclusion Extraction Model (based on sequence classification)
+
+#### How to use
+
 ```python
 from transformers import  RobertaTokenizerFast, AutoModelForSequenceClassification
 from datasets  import load_dataset, Dataset
@@ -40,8 +44,17 @@ window_size = 5
 context_l = create_windowed_context(raw_dataset, window_size)
 raw_dataset_window = raw_dataset.map(partial(create_windowed_context_ds, context_l), batched=False, with_indices=True)
 tokenized_data = raw_dataset_window.map(tokenize_function, batched=True)
+```
 
 
+### Citing
 
-
+If you use HeConE in your research, please cite [HeRo: RoBERTa and Longformer Hebrew Language Models](http://arxiv.org/abs/2304.11077).
+```
+@article{shalumov2023hero,
+      title={HeRo: RoBERTa and Longformer Hebrew Language Models}, 
+      author={Vitaly Shalumov and Harel Haskey},
+      year={2023},
+      journal={arXiv:2304.11077},
+}
 ```