/LiteLanguageModel

LiteLanguageModel is a simplified version of a large language model, developed with educational purposes in mind. It aims to provide insights into the inner workings of language processing using deep learning technologies, focusing on the core concepts of transformer architecture.

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LiteLanguageModel

LiteLanguageModel is a simplified version of a large language model, developed with educational purposes in mind. It aims to provide insights into the inner workings of language processing using deep learning technologies, focusing on the core concepts of transformer architecture.

Getting Started

These instructions will get you a copy of the project up and running on your local machine for development and testing purposes.

Prerequisites

What things you need to install the software and how to install them:

  • Python 3.8 or higher
  • CUDA Toolkit 11.2 or higher (if you plan to run the model on GPU)
  • Required Python libraries: numpy, torch, transformers

Installing

A step-by-step series of examples that tell you how to get a development environment running:

  1. Clone the repository:

    git clone https://github.com/yourusername/LiteLanguageModel.git

  2. Install the required Python packages:

    cd LiteLanguageModel
pip install -r requirements.txt

  3. Verify the installation by running a simple test:

    python test.py

Usage

Provide instructions on how to use the model, including any scripts for training, testing, or inference. For example:

python train.py --data_path "data/my_dataset.txt" --epochs 5 --batch_size 32

Tips

Stay Updated: If the TensorLite repository updates, you can update your submodule to the latest commit by:

git submodule update --remote TensorLite
git commit -am "Updated TensorLite submodule to latest"
git push

Initialization for New Clones: initialize and update the submodules:

git clone --recurse-submodules https://github.com/SyedAman/LiteLanguageModel.git

Contributing

Please read CONTRIBUTING.md for details on our code of conduct, and the process for submitting pull requests to us.

Versioning

We use SemVer for versioning. For the versions available, see the tags on this repository.

Authors

See also the list of contributors who participated in this project.

License

This project is licensed under the MIT License - see the LICENSE.md file for details.

Acknowledgments

  • Hat tip to anyone whose code was used
  • Inspiration
  • etc.