Mistral 7B Fine-Tuning with Q-Lora and Chain-of-Thought Dataset
Offered By: The Machine Learning Engineer via YouTube
Course Description
Overview
Learn how to fine-tune the Mistral7B v2 model using QLora and a Chain-of-Thought (CoT) dataset in this comprehensive video tutorial. Explore the process of implementing Chain-of-Thought Fine-Tuning to enhance the model's performance. Access the provided GitHub notebooks for hands-on practice and detailed implementation steps. Gain valuable insights into advanced machine learning techniques and expand your data science skills through this practical demonstration.
Syllabus
Mistral 7B Fine Tuning Q-Lora CoT Dataset #datascience #machinelearning
Taught by
The Machine Learning Engineer
Related Courses
TensorFlow: Working with NLPLinkedIn Learning Introduction to Video Editing - Video Editing Tutorials
Great Learning via YouTube HuggingFace Crash Course - Sentiment Analysis, Model Hub, Fine Tuning
Python Engineer via YouTube GPT3 and Finetuning the Core Objective Functions - A Deep Dive
David Shapiro ~ AI via YouTube How to Build a Q&A AI in Python - Open-Domain Question-Answering
James Briggs via YouTube