LoRA & PEFT: The Easy Way to Fine-Tune LLMs
Автор: PyInsightsVerse
Загружено: 2026-01-30
Просмотров: 5
Описание:
LoRA & PEFT: The Easy Way to Fine-Tune LLMs
Want to fine-tune an LLM without needing a massive GPU?
In this video, I show you how to use Parameter-Efficient Fine-Tuning (PEFT) to adapt the Qwen2-0.5B language model for your own tasks.
Instead of updating billions of parameters, we train only a tiny fraction of the model using techniques like LoRA, making fine-tuning faster, cheaper, and possible on consumer hardware.
You’ll learn:
-Fine-tuning techniques
-What PEFT is and why it matters
-How LoRA reduces memory usage during fine-tuning
-How to set up the Qwen2-0.5B model with Hugging Face
-Step-by-step PEFT training code
-How to test your fine-tuned mode
Notebook available at:
📁 Github: https://github.com/enomis-dev/YouTube...
Timestamps:
(0:00) Intro
(0:05) What does fine-tuning mean?
(0:52) Approches for fine-tuning
(3:43) LORA
(4:14) Model-Prep
(4:39) Test model pre fine-tuning
(5:16) PEFT fine-tuning
(9:25) Improvements
(9:58) Outro
Intro and Outro
music: https://mixkit.co/free-sound-effects/... Cinematic transition brass hum
video: https://www.pexels.com/video/the-sun-...
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