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license: mit
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## license: mit

# VerseFormer

VerseFormer is a GPT-style transformer language model implemented in PyTorch and trained on Shakespeare's literary works.

The project was developed to explore transformer architectures, self-attention mechanisms, token embeddings, and autoregressive text generation through hands-on implementation and experimentation.

## Overview

VerseFormer learns patterns in Shakespearean text and generates text by predicting the next token in a sequence.

## Features

* GPT-style transformer architecture
* Implemented using PyTorch
* Autoregressive next-token prediction
* Shakespeare-trained language model
* Text generation capability
* Custom training pipeline

## Architecture

The model includes:

* Token Embeddings
* Positional Embeddings
* Multi-Head Self-Attention
* Feed-Forward Networks
* Layer Normalization
* Residual Connections

## Training Data

The model was trained on Shakespeare's plays, sonnets, and poems to learn language structure, context, and literary style.

## Technologies Used

* Python
* PyTorch
* NumPy

## Learning Outcomes

This project helped develop practical understanding of:

* Transformer architectures
* Attention mechanisms
* Language modeling
* Deep learning workflows
* Model training and experimentation

## Example

Input:

To be, or not to be

Possible Output:

To be, or not to be, that is the question whether...

*Generated output may vary depending on training configuration.*

## Author

**Anurag Verma**

* GitHub: https://github.com/anuragverma81
* LinkedIn: https://www.linkedin.com/in/anurag-verma-8943162b5
* 
## License

MIT License