readme_content = """

Vision Transformer on CIFAR-10

Overview

This project implements a Vision Transformer (ViT) model for image classification on the CIFAR-10 dataset.

Dataset

• CIFAR-10: 60,000 32x32 color images in 10 classes.
• Training images: 50,000
• Test images: 10,000

Notebook

The main notebook is located in the notebooks/ folder:

• VisionTransformers_CIFAR10.ipynb

You can run it directly on Google Colab.

Installation

Install required dependencies with:

pip install -r requirements.txt




---

### **Step 4 — Git: Pull, Add, Commit, Push**
```python
# Pull remote changes, allow unrelated histories
!git pull origin main --allow-unrelated-histories

# Stage all changes
!git add .

# Commit changes
!git commit -m "Add Vision Transformer CIFAR10 notebook and update README"

# Push to GitHub
!git push origin main