Improve dataset card: Update task category, add tags, and add sample usage

README.md

@@ -1,4 +1,17 @@
 ---
+task_categories:
+- image-text-to-text
+tags:
+- multimodal
+- mllm
+- geometric-reasoning
+- visual-question-answering
+- shape-recognition
+- chain-of-thought
+- mathematics
+- reasoning
+language:
+- en
 dataset_info:
   features:
   - name: shape
@@ -40,8 +53,6 @@ configs:
     path: data/heptagons_with_visual_cues-*
   - split: arrow_on_plus_with_visual_cues
     path: data/arrow_on_plus_with_visual_cues-*
-task_categories:
-- image-classification
 library_name:
 - pytorch
 ---
@@ -56,6 +67,19 @@ This dataset is part of the work **"Forgotten Polygons: Multimodal Large Languag
 
 This dataset is designed to evaluate the shape understanding capabilities of Multimodal Large Language Models (MLLMs).
 
+## Sample Usage
+
+This dataset is designed to be used with the evaluation code provided in the [GitHub Repository](https://github.com/rsinghlab/Shape-Blind/tree/main). To evaluate MLLMs on various tasks using this dataset, follow the instructions in the `evaluation` folder of the repository.
+
+For example, to run a shape identification task using LLaVA-1.5:
+
+```bash
+# Navigate to the 'evaluation' folder in the cloned GitHub repository
+cd Shape-Blind/evaluation
+# Run the evaluation script
+python3 evaluate_MLLMs.py --model_version llava-1.5 --task shape_id --dataset_size full
+```
+
 ## Dataset Splits
 
 Each split corresponds to a different reasoning task and shape identification challenge.