Metadata-Version: 2.1
Name: nexus-deep-learning
Version: 0.1.0
Summary: A modular deep learning library for implementing AI research papers
Home-page: https://github.com/yourusername/nexus
Author: Your Name
Author-email: your.email@example.com
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Science/Research
Classifier: License :: OSI Approved :: MIT License
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Requires-Python: >=3.7
Description-Content-Type: text/markdown
Requires-Dist: torch>=1.9.0
Requires-Dist: torchvision>=0.10.0
Requires-Dist: numpy>=1.19.0
Requires-Dist: pynvml>=11.0.0
Requires-Dist: PyYAML>=5.4.1
Requires-Dist: tqdm>=4.62.0
Requires-Dist: pillow>=8.3.0
Requires-Dist: scikit-learn>=0.24.0
Requires-Dist: faiss-cpu>=1.7.0
Requires-Dist: datasets>=2.14.0

# Nexus Deep Learning Library

Nexus is a modular deep learning library built on PyTorch that enables rapid implementation of state-of-the-art AI research papers. It provides reusable components across multiple domains including NLP, Computer Vision, Reinforcement Learning, and Robotics.

## Key Features

- 🧠 Modular implementation of popular deep learning architectures
- 🔄 Mix-and-match components across different domains
- ⚡ Efficient training with automatic mixed precision and distributed training support
- 🎯 Ready-to-use examples for common tasks
- 📦 Built-in caching and streaming data pipelines

## Installation

```bash
pip install nexus-deep-learning
```

## Quick Start

```python
from nexus.models.cv import VisionTransformer
from nexus.training import Trainer
```

### Create model

```python
model = VisionTransformer(config={
"image_size": 224,
"patch_size": 16,
"num_classes": 1000,
"embed_dim": 768,
"num_layers": 12,
"num_heads": 12
})
```

### Train model

```python
trainer = Trainer(model=model, config={
    "dataset": "imagenet",
    "batch_size": 128,
    "num_epochs": 100
})
```

### Documentation
