Large Language Models for Scientific Research

An introduction to large language models for scientific research - how do they work, how can they be used, and how can they be trained?

Check out the notebooks · Check out the Slides
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Head to the workshop materials »

Table of Contents

1. Overview
2. Prerequisites
3. Contributing
4. License

Overview

This repository is Part I of a two-part course:

1. An introduction to large language models for scientific research - how do they work, how can they be used, and how can they be trained?
2. A hands-on tutorial on how to use large language models for scientific research.

Introduction to LLMs

Part 1 consists of some slides and some notebooks that introduce LLMs, and how they can be used for scientific research.

If you head to the website, you can find the slides that we used in the workshop. You can also find them in the Slides folder in this repository.

There are also some notebooks - we look at finetuning a BERT model for classication tasks, finetuning GPT-2 to make it sound like the President of the United States, and using RAG to produce a simple question-answering system with Streamlit

Hands-on LLM workshop

Part 2 is a much more comprehensive hands-on tutorial. It is designed as a reference source for our hands-on LLM workshop, but may be useful for others to get started with LLMs. To get started, follow the link and head to the website.

Hands On Course »

Prerequisites

This project assumes essentially no knowledge of language models and does not require an understanding of the underlying mathematics or programming languages.

Development of this material is an ongoing process, and given the rapid advancement of LLM libraries may contain bugs or out of date information. If you find any issues, please raise an Issue via GitHub, and we will endeavour to address it as soon as possible. Thank you!

Contributing

Contributions are what make the open source community such an amazing place to learn, inspire, and create. Any contributions you make are greatly appreciated.

If you have a suggestion that would make this better, please fork the repo and create a pull request. You can also simply open an issue with the tag "enhancement". Don't forget to give the project a star! Thanks again!

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

License

Distributed under a GPL-3.0 License. See LICENSE for more information.

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