Discover the secrets to effortlessly fine-tuning Language Models (LLMs) with your own data in our latest tutorial video. We dive into a cost-effective and surprisingly simple process, leveraging the power of Hugging Face and Unsloth libraries for unmatched memory efficiency and flexibility in model training. Our walkthrough covers everything from selecting the right model on the Hugging Face Hub to preparing your data and tuning it with Colab resources, including a free tier option. This guide is designed to demystify the fine-tuning process, making it accessible even to beginners.

Join us as we explore the use of Mistral 7B model and demonstrate how to maximize your fine-tuning outcomes with minimal costs.

Modeling Tool: https://softwaresim.com
Demonstration Code and Diagram: https://github.com/nodematiclabs/mist...

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0:00 Conceptual Overview
3:02 Custom Data Preparation
8:17 Fine Tuning Notebook (T4)
16:52 Fine Tuning Notebook (A100)
19:13 Hugging Face Save and Usage