Finetuning Transformer Models

Master the art of LLM finetuning with LoRA, QLoRA, and Hugging Face. Learn how to prepare, train and optimize models for specific tasks efficiently.

Built in partnership withHugging Face
  • Skill level

  • Time to complete

    Average based on combined completion rates — individual pacing in lessons, projects, and quizzes may vary
    2 hours
  • Certificate of completion

    Included with paid plans
  • Prerequisites

    1 course
    We suggest you complete the following courses before you get started with Finetuning Transformer Models:
    • Intro to AI Transformers

About this course

Finetuning is an essential skill in the world of Large Language Models (LLMs), allowing you to customize pre-trained transformer models for specific tasks. This course will guide you through the practical process of finetuning using popular tools like LoRA, quantization, and QLoRA, using Hugging Face libraries and the popular Mistral series of open-weight LLMs. You’ll learn about the life cycle of finetuning, GPU usage in deep learning, and parameter-efficient finetuning (PEFT).

Skills you'll gain

  • Learn how to prepare training data for finetuning

  • Understand how to perform full finetunes using Hugging Face

  • Get hands-on experience with PEFT and 4-bit quantization techniques


3 lessons • 2 quizzes

The platform

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Frequently asked questions about Finetuning Transformer Models

  • Finetuning is the process of training a pre-trained deep learning model further using your own custom data, resulting in a customized (“finetuned”) model.

Join over 50 million learners and start Finetuning Transformer Models today!

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