Update README.md

README.md

@@ -111,22 +111,21 @@ Furthermore, we find that LLMs perform better in their local languages for mid-t
 
 ## Requirements
 ```Python
-datasets >= 2.19.2
-pandas >= 2.1.4
+datasets == 2.19.2
+pandas == 2.1.4
 ```
 
 ## Dataset
 All the data samples for short-answer questions, including the human-annotated answers, can be found in the `data/` directory.
 Specifically, the annotations from each country are included in the `annotations` split, and each country/region's data can be accessed by **[country codes](https://huggingface.co/datasets/nayeon212/BLEnD#countryregion-codes)**. 
 ```Python
-import pandas as pd
+from datasets import load_dataset
 
 # Login using e.g. `huggingface-cli login` to access this dataset
-splits = {'DZ': 'data/annotations_hf/Algeria_data.json', 'AS': 'data/annotations_hf/Assam_data.json', 'AZ': 'data/annotations_hf/Azerbaijan_data.json', 'CN': 'data/annotations_hf/China_data.json', 'ET': 'data/annotations_hf/Ethiopia_data.json', 'GR': 'data/annotations_hf/Greece_data.json', 'ID': 'data/annotations_hf/Indonesia_data.json', 'IR': 'data/annotations_hf/Iran_data.json', 'MX': 'data/annotations_hf/Mexico_data.json', 'KP': 'data/annotations_hf/North_Korea_data.json', 'NG': 'data/annotations_hf/Northern_Nigeria_data.json', 'KR': 'data/annotations_hf/South_Korea_data.json', 'ES': 'data/annotations_hf/Spain_data.json', 'GB': 'data/annotations_hf/UK_data.json', 'US': 'data/annotations_hf/US_data.json', 'JB': 'data/annotations_hf/West_Java_data.json'}
-df = 
+ds = load_dataset("nayeon212/BLEnD", "short-answer-questions")
 
 # To access data from Assam:
-assam_annotations = pd.read_json("hf://datasets/nayeon212/BLEnD/" + splits["AS"])
+ds_as = ds['AS']
 ```
 Each file includes a JSON variable with question IDs, questions in the local language and English, the human annotations both in the local language and English, and their respective vote counts as values. The same dataset for South Korea is shown below:
 ```JSON