Update README.md

README.md

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 WAON-Bench is a manually curated image classification dataset designed to benchmark Vision-Language models on Japanese culture.
 The dataset contains 374 classes across 8 categories (animals, buildings, events, everyday life, food, nature, scenery, and traditions), with 5 images per class, totaling 1,870 examples.
 
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 ## How to Use
+⚠️ This repository is a mirror of the original dataset hosted at https://gitlab.llm-jp.nii.ac.jp/datasets/WAON-Bench
+
+Due to copyright restrictions, WAON-Bench dataset with images is hosted only on a domestic server and are not included in this mirror.
 
+To use WAON-Bench, first download the dataset from:
+```python
+git clone https://gitlab.llm-jp.nii.ac.jp/datasets/WAON-Bench
+mv WAON-Bench/data .
+```
+After placing the dataset directory locally, you can load each dataset using the 🤗 datasets library:
 ```python
 from datasets import load_dataset
 
-ds = load_dataset("llm-jp/WAON-Bench")
+ds = load_dataset("data")
 ```
 
 ## Data Collection Pipeline