Fine-Tune LLM in VS Code AI Toolkit Locally on Custom Dataset
In this video by Fahd Mirza, viewers are guided through the process of fine-tuning a large language model (LLM) locally using Visual Studio Code (VS Code) with the AI Toolkit. The tutorial focuses on fine-tuning a model on a custom dataset, leveraging the capabilities of VS Code’s AI Toolkit, which integrates tools and models from Azure AI Studio and Hugging Face.
The video begins with an introduction to the VS Code AI Toolkit, which simplifies the development of generative AI applications by providing access to various AI models and tools. Fahd highlights the ability to browse, download, fine-tune, test, and deploy models locally or to the Azure Cloud using this toolkit.
Before diving into the tutorial, Fahd gives a shoutout to Mast Compute for sponsoring the GPU used in the video, specifically an NVIDIA RTX A6000 with 48 GB of VRAM. He also outlines the prerequisites for the tutorial, such as having the Windows Subsystem for Linux (WSL) for Windows users, and the necessity of a GPU for fine-tuning tasks.