Update README.md
Browse files
README.md
CHANGED
@@ -1,3 +1,39 @@
|
|
1 |
---
|
2 |
license: cc-by-sa-4.0
|
|
|
|
|
|
|
|
|
|
|
3 |
---
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
---
|
2 |
license: cc-by-sa-4.0
|
3 |
+
datasets:
|
4 |
+
- sinhala-nlp/NSINA-Headlines
|
5 |
+
- sinhala-nlp/NSINA
|
6 |
+
language:
|
7 |
+
- si
|
8 |
---
|
9 |
+
|
10 |
+
# Sinhala Headline Generation
|
11 |
+
This is a text generation task created with the [NSINA dataset](https://github.com/Sinhala-NLP/NSINA). This dataset is also released with the same license as NSINA. The objective of the task is to generate news headlines based on the provided news content.
|
12 |
+
|
13 |
+
|
14 |
+
## Data
|
15 |
+
We used the same instances from NSINA 1.0 as all the news articles had headlines. We divided this dataset into a training and test set following a 0.8 split.
|
16 |
+
Data can be loaded into pandas dataframes using the following code.
|
17 |
+
|
18 |
+
```python
|
19 |
+
from datasets import Dataset
|
20 |
+
from datasets import load_dataset
|
21 |
+
|
22 |
+
train = Dataset.to_pandas(load_dataset('sinhala-nlp/NSINA-Headlines', split='train'))
|
23 |
+
test = Dataset.to_pandas(load_dataset('sinhala-nlp/NSINA-Headlines', split='test'))
|
24 |
+
```
|
25 |
+
|
26 |
+
|
27 |
+
|
28 |
+
## Citation
|
29 |
+
If you are using the dataset or the models, please cite the following paper.
|
30 |
+
|
31 |
+
~~~
|
32 |
+
@inproceedings{Nsina2024,
|
33 |
+
author={Hettiarachchi, Hansi and Premasiri, Damith and Uyangodage, Lasitha and Ranasinghe, Tharindu},
|
34 |
+
title={{NSINA: A News Corpus for Sinhala}},
|
35 |
+
booktitle={The 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)},
|
36 |
+
year={2024},
|
37 |
+
month={May},
|
38 |
+
}
|
39 |
+
~~~
|