Transformer

This repository contains the implementation of a Transformer model. The code is written in Python.

Demo

Project Structure

The project is organized into the following directories and files:

Files

• model: Contains the core components of the Transformer model.
  • attention.py: Implements the attention mechanism.
  • decoder.py: Implements the decoder part of the Transformer.
  • embedding.py: Implements the embedding layer.
  • encoder.py: Implements the encoder part of the Transformer.
  • feedforward.py: Implements the feedforward neural network.
  • loss.py: Contains the loss function used for training.
  • multi_head_attention.py: Implements multi-head attention.
  • transformer.py: Assembles the full Transformer model.
• 3_transformer.ipynb: Jupyter notebook demonstrating the use of the Transformer model.

Installation

To run this project, you will need Python and the dependencies listed in requirements.txt. You can install them using pip: