Update README.md

README.md

@@ -23,9 +23,19 @@ configs:
 ---
 
 # WAON-Bench: Japanese Cultural Image Classification Dataset
+
+<img src="WAON-Bench.jpg" alt="Overview of WAON-Bench" width="80%"/>
+
 WAON-Bench is a manually curated image classification dataset designed to benchmark Vision-Language models on visual understanding of Japanese culture.
 It comprises 374 classes, each containing 5 images, covering a diverse range of cultural, natural, and everyday aspects of Japanese life.
 
+## How to Use
+
+```python
+from datasets import load_dataset
+
+ds = load_dataset("speed/WAON-Bench")
+```
 
 ## Data Collection Pipeline
 We followed the pipeline below to construct the dataset:
@@ -71,6 +81,12 @@ Example:
 | scenery  | '茶畑', '雪国の街並み', '漁港', '砂防ダム', '石垣', ...|
 | tradition| '華道', 剣道', '柔道', '弓道', ...|
 
+- **t-SNE Visualization of SigLIP2 Embeddings**
+
+
+The figure below shows a 2D t-SNE projection of image embeddings generated using [google/siglip2-base-patch16-256](https://huggingface.co/google/siglip2-base-patch16-256). Each point represents one image in the dataset. 
+
+<img src="siglip_tsne_visualization.png" alt="t-SNE Visualization" width="50%"/>