YoVDO

Leveraging Open-Source LLMs for Production

Offered By: Data Science Dojo via YouTube

Tags

Machine Learning Courses Reinforcement Learning Courses Code Generation Courses Quantization Courses Model Optimization Courses Fine-Tuning Courses

Course Description

Overview

Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only!
Explore the world of open-source Large Language Models (LLMs) and their practical applications in this comprehensive 1-hour 7-minute webinar. Gain insights into the comparative analysis between open-source LLMs and proprietary options like OpenAI, understand the economic aspects of hosting these models, and learn how to evaluate and benchmark LLM performance. Delve into topics such as code generation, memory calculation, quantization, Llama 2 latency and cost, supervised fine-tuning, reinforcement learning for human feedback, and the differences between RLHF and DPO. Discover the potential of open-source LLMs for production environments and explore tools like dstack to enhance your understanding of this rapidly evolving field.

Syllabus

Introduction
Why open-source LLMs?
Major open-source LLMs
Code generation
Memory calculator
Quantization
Llama 2 latency and cost
Supervised fine-tuning
Reinforcement learning for human feedback
RLHF vs DPO
dstack


Taught by

Data Science Dojo

Related Courses

Computational Neuroscience
University of Washington via Coursera
Reinforcement Learning
Brown University via Udacity
Reinforcement Learning
Indian Institute of Technology Madras via Swayam
FA17: Machine Learning
Georgia Institute of Technology via edX
Introduction to Reinforcement Learning
Higher School of Economics via Coursera