Fine-tuning LLMs Without Maxing Out Your GPU - LoRA for Parameter-Efficient Training
Data Centric via YouTube
Overview
Learn how to utilize LoRA (Low Rank Adapters) for parameter-efficient fine-tuning of large language models in this 47-minute video. Follow along as the instructor demonstrates fine-tuning RoBERTa to classify consumer finance complaints using Google Colab with a V100 GPU. Gain insights into the end-to-end process, including access to a detailed notebook and technical blog. Discover how to optimize your GPU usage while achieving effective model fine-tuning. Explore additional resources on building LLM-powered applications, understanding precision and recall, and booking consultations for further guidance.
Syllabus
Fine-tune your LLMs, Without Maxing out Your GPU!
Taught by
Data Centric