Embeddings vs Fine-Tuning - Supervised Fine-tuning - Part 2
Offered By: Trelis Research via YouTube
Course Description
Overview
Dive into the second part of a comprehensive video tutorial on embeddings and fine-tuning, focusing on supervised fine-tuning. Learn how to effectively implement fine-tuning techniques, understand the differences between chat and base models, and explore supervised versus unsupervised approaches. Discover methods for converting datasets into Q&A format and practice supervised fine-tuning using Google Colab. Gain valuable pro tips and access scripts and GitHub repositories to enhance your learning experience. Follow along with presentation slides and a Llama 2 Inference Notebook to compare chat and base models.
Syllabus
Part 2: Supervised Fine-tuning
How to make fine-tuning work?
How NOT to do fine-tuning
Video Overview
Chat vs Base models
Supervised versus Unsupervised fine-tuning
Converting a dataset into Q&A
Supervised fine-tuning in google colab.
Pro tips
Scripts and GitHub Repo Access
Taught by
Trelis Research
Related Courses
Introduction to Artificial IntelligenceStanford University via Udacity Natural Language Processing
Columbia University via Coursera Probabilistic Graphical Models 1: Representation
Stanford University via Coursera Computer Vision: The Fundamentals
University of California, Berkeley via Coursera Learning from Data (Introductory Machine Learning course)
California Institute of Technology via Independent