Create a Clone of Yourself With a Fine-tuned LLM

This article aims to illustrate how to fine-tune a top-performing LLM efficiently and cost-effectively on a custom dataset. We will explore the utilization of the Falcon-7B model with LoRA adapters using Lit-GPT. Ever wondered what it would be like to have a digital twin? A virtual replica of yourself that can have conversations, learn, and even reflect your thoughts? Recent advances in artificial intelligence (AI) have made this once-futuristic idea attainable. The AI community’s effort has led to the development of many high-quality open-source LLMs, including but not limited to Open LLaMA, Falcon, StableLM, and Pythia. You can fine-tune these models on a custom instruction dataset to adapt to your specific task, such as training a chatbot to answer financial questions. Furthermore, it can also provide a data privacy advantage when data cannot be uploaded or shared with cloud APIs. <a href="https://medium.com/better-programming/unleash-your-digital-twin-how-fine-tuning-llm-can-create-your-perfect-doppelganger-b5913e7dda2e">Read More</a>