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README.md

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 ---
+language: en
+license: mit
+multilinguality: monolingual
+task_categories:
+- image-classification
+task_ids:
+- multi-class-image-classification
+pretty_name: MNIST
 dataset_info:
   features:
   - name: image
@@ -22,3 +30,36 @@ configs:
   - split: test
     path: data/test-*
 ---
+
+# 🖼️ MNIST (Extracted from PyTorch Vision)
+
+MNIST is a classic dataset of handwritten digits, widely used for image classification tasks in machine learning.
+
+## ℹ️ Dataset Details
+
+## 📖 Dataset Description
+
+The MNIST database of handwritten digits is a commonly used benchmark dataset in machine learning. It consists of 70,000 grayscale images of handwritten digits (0-9), each with a size of 28x28 pixels. The dataset is split into 60,000 training images and 10,000 testing images. MNIST is often used for evaluating and comparing different machine learning algorithms, particularly in the field of image recognition.
+
+## 📂 Dataset Structure
+
+Each data point is a pair:
+
+- **image:** A visual captured (stored as a PIL Image).
+- **label:** The corresponding label (an integer representing the class).
+
+## 🚀 How to Use this Dataset
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset('MNIST')
+```
+
+## 🗄️ Source Data
+
+Auto-generated from PyTorch Vision, please check the original [MNIST](http://yann.lecun.com/exdb/mnist/) for more info.
+
+## 📜 License
+
+mit