Update README.md

README.md

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----
-license: mit
----
+---
+license: mit
+language:
+- en
+tags:
+- gan
+- mnist
+- 7gen
+- pytorch
+library_name: torch
+model_type: image-generator
+---
+
+![7Gen Model](https://img.shields.io/badge/7Gen-MNIST_Generator-blue?style=for-the-badge)
+![Python](https://img.shields.io/badge/python-3.8+-blue.svg?style=for-the-badge&logo=python)
+![PyTorch](https://img.shields.io/badge/PyTorch-1.12+-red.svg?style=for-the-badge&logo=pytorch)
+![License](https://img.shields.io/badge/license-MIT-green.svg?style=for-the-badge)
+
+# 7Gen - Advanced MNIST Digit Generation System
+
+**State-of-the-art Conditional GAN for MNIST digit synthesis with self-attention mechanisms.**
+
+---
+
+## 🚀 Features
+
+- 🎯 **Conditional Generation**: Generate specific digits (0–9) on demand.
+- 🖼️ **High Quality Output**: Sharp and realistic handwritten digit samples.
+- ⚡ **Fast Inference**: Real-time generation on GPU.
+- 🔌 **Easy Integration**: Minimal setup, PyTorch-native implementation.
+- 🚀 **GPU Acceleration**: Full CUDA support.
+
+---
+
+## 🔍 Model Details
+
+- **Architecture**: Conditional GAN with self-attention  
+- **Parameters**: 2.5M  
+- **Input**: 100-dimensional noise vector + class label  
+- **Output**: 28x28 grayscale images  
+- **Training Data**: MNIST dataset (60,000 images)  
+- **Training Time**: ~2 hours on NVIDIA RTX 3050 Ti  
+
+---
+
+## 🧪 Performance Metrics
+
+| Metric           | Score |
+|------------------|-------|
+| **FID Score**    | 12.3  |
+| **Inception Score** | 8.7   |
+
+- **Training Epochs**: 100  
+- **Batch Size**: 64  
+
+---
+
+## ⚙️ Training Configuration
+
+```yaml
+model:
+  latent_dim: 100
+  num_classes: 10
+  generator_layers: [256, 512, 1024]
+  discriminator_layers: [512, 256]
+
+training:
+  batch_size: 64
+  learning_rate: 0.0002
+  epochs: 100
+  optimizer: Adam
+  beta1: 0.5
+  beta2: 0.999