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README.md

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+# siqa Dataset
+
+## Overview
+This repository contains the processed version of the siqa dataset. The dataset is formatted as a collection of multiple-choice questions.
+
+## Dataset Structure
+Each example in the dataset contains the following fields:
+```json
+{
+  "id": 0,
+  "question": "Tracy didn't go home that evening and resisted Riley's attacks. What does Tracy need to do before this?",
+  "choices": [
+    "make a new plan",
+    "Go home and see Riley",
+    "Find somewhere to go"
+  ],
+  "answerID": 2
+}
+```
+
+## Fields Description
+- `id`: Unique identifier for each example
+- `question`: The question or prompt text
+- `choices`: List of possible answers
+- `answerID`: Index of the correct answer in the choices list (0-based)
+
+## Loading the Dataset
+You can load this dataset using the Hugging Face datasets library:
+```python
+from datasets import load_dataset
+
+# Load the dataset
+dataset = load_dataset("DatologyAI/siqa")
+
+# Access the data
+for example in dataset['train']:
+    print(example)
+```
+
+## Example Usage
+```python
+# Load the dataset
+dataset = load_dataset("DatologyAI/siqa")
+
+# Get a sample question
+sample = dataset['train'][0]
+
+# Print the question
+print("Question:", sample['question'])
+print("Choices:")
+for idx, choice in enumerate(sample['choices']):
+    print(f"{idx}. {choice}")
+print("Correct Answer:", sample['choices'][sample['answerID']])
+```