Update README.md

README.md

@@ -97,6 +97,7 @@ configs:
 This is the official repository of **[BLEnD: A Benchmark for LLMs on Everyday Knowledge in Diverse Cultures and Languages](https://arxiv.org/abs/2406.09948)** (Submitted to NeurIPS 2024 Datasets and Benchmarks Track).
 
 *24/12/05: Updated translation errors*
+*25/05/02: Updated multiple choice questions file (v1.1)*
 
 ## About
 ![BLEnD Construction & LLM Evaluation Framework](main_figure.png)
@@ -118,12 +119,14 @@ pandas >= 2.1.4
 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
-from datasets import load_dataset
+import pandas as pd
 
-annotations = load_dataset("nayeon212/BLEnD",'annotations')
+# 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 = 
 
 # To access data from Assam:
-assam_annotations = annotations['AS']
+assam_annotations = pd.read_json("hf://datasets/nayeon212/BLEnD/" + splits["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