DataHour: LLM Fine Tuning with PEFT Techniques

Explore the realm of Language Models (LLMs) and their transformative impact as we unravel their inner workings and delve into the significance of fine-tuning. Discover the power of the PEFT (Prompt Engineering and Fine Tuning) technique, a game-changer in the world of LLMs. From understanding the nuances of training versus fine-tuning to mastering Prompt Engineering, this session will guide you through the intricacies.

Learn about QLORA (Query-Level Optimization for Response Ambiguity) and how it enhances precision in LLM responses. Gain practical insights into the step-by-step process of Tuning using PEFT strategies, from data preprocessing to crafting effective prompts.

Prerequisites: It is beneficial to have a basic familiarity with Machine Learning and Large Language Models for this webinar.

Awadhesh is a dynamic computer vision and machine learning enthusiast and researcher, driven by a passion for exploring the vast realm of CV and ML at scale with AWS. With a Master of Technology (M.Tech.) degree in Computer Application from the prestigious Indian Institute of Technology, Delhi, he brings a robust academic foundation to his professional journey. Currently serving as a Senior Data Scientist at Kellton Tech Solutions Limited and having previously excelled in roles at AdGlobal360 and as an Assistant Professor at KIET Group of Institutions, Awadhesh's commitment to innovation and his contributions to the field make him an invaluable asset to any organisation seeking expertise in CV/ML projects.