Skip to Main Content

LLMs and GenAI in Digital Scholarship

An overview of how to use LLMs and GenAI in research and instruction.

Fine-Tuning LLMs Tutorials

Fine-Tuning LLMs: A Guide With Examples

A beginner-friendly tutorial that walks you through the process of fine-tuning GPT-2 using Hugging Face's Transformers library. It covers data preparation, model selection, and evaluation, making it ideal for those new to LLM fine-tuning.

Fine-Tuning LLMs Guide | Unsloth Documentation

This guide provides step-by-step instructions for fine-tuning LLMs like Llama-3.1-8B on platforms such as Google Colab and Kaggle. It emphasizes parameter-efficient techniques, allowing for fine-tuning with as little as 3GB of VRAM.

Fine-Tuning Large Language Models (LLMs) | w/ Example Code

A comprehensive video tutorial that demonstrates fine-tuning techniques for LLMs, including QLoRA and reinforcement learning from human feedback (RLHF). The session includes hands-on code examples, making it an excellent resource for visual learners.

Fine-Tuning LLM Models Course

This comprehensive course by Krish Naik covers advanced fine-tuning techniques such as QLoRA and LoRA, as well as quantization methods using Llama2 and Google's Gemma model. It also explores building LLM pipelines with no-code tools, making it ideal for researchers seeking both theoretical insights and practical implementation strategies.

Let's Build GPT: From Scratch, in Code, Spelled Out

In this in-depth video, Andrej Karpathy provides a step-by-step guide to constructing a GPT-style model from the ground up, including the fine-tuning process. His clear explanations and code walkthroughs are particularly beneficial for those in academia aiming to understand the underlying mechanics of LLMs.

EASIEST Way to Fine-Tune a LLM and Use It With Ollama

Learn how to fine-tune LLMs in Python for use in Ollama. Walk through it step by step, with all the code, and learn how to test it out.

GenAI is an evolving field with many options depending on your research goals, and on the tools and environments you wish to work in. Each of these tutorials showcases different platforms and techniques, providing a broad range of approaches. For additional resources or for more tailored guidance and assistance, feel free to reach out to the Freedman Center at FreedmanCenter@case.edu.