Fine-tuning LLMs Without Maxing Out Your GPU - LoRA for Parameter-Efficient Training
Offered By: Data Centric via YouTube
Course Description
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
Related Courses
How to Do Stable Diffusion LORA Training by Using Web UI on Different ModelsSoftware Engineering Courses - SE Courses via YouTube MicroPython & WiFi
Kevin McAleer via YouTube Building a Wireless Community Sensor Network with LoRa
Hackaday via YouTube ComfyUI - Node Based Stable Diffusion UI
Olivio Sarikas via YouTube AI Masterclass for Everyone - Stable Diffusion, ControlNet, Depth Map, LORA, and VR
Hugh Hou via YouTube