By the end of this course, a learner will have a solid understanding of Large Language Models running locally. You'll be able to setup a local environment using powerful tooling to run different LLMs and interact with them both with a web interface as well as with APIs.
Foundations of Local Large Language models
Foundations of Local Large Language models
Instructors: Noah Gift
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Gain insight into a topic and learn the fundamentals.
4.6
(10 reviews)
Beginner level
Recommended experience
23 hours to complete
3 weeks at 7 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Local Large Language Models (LLMs)
Tools for running LLMs locally like Llamafile
Skills you'll gain
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Assessments
9 assignments
Taught in English
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There are 3 modules in this course
This week, you will learn mitigation strategies, evaluate task performance, and operationalize workflows by identifying risks in notebooks and deploying an LLM application.
What's included
21 videos16 readings4 assignments1 discussion prompt1 ungraded lab
This week, you will explore different types of generative AI applications, including API-based, embedded model, and multi-model systems. You'll learn the fundamentals of building robust applications using techniques like Retrieval Augmented Generation (RAG) to improve context. Through hands-on exercises, you'll gain experience evaluating real-world performance of large language models using Elo ratings coded in Python, Rust, R, and Julia. Then you'll explore production LLM workflows using tools like skypilot, Lorax, and Ludwig for fine-tuning models like Mistral-7b. Finally, you'll gain hands-on experience testing an application locally and deploying it on the cloud.
What's included
13 videos13 readings4 assignments4 ungraded labs
This week you will learn foundations of generative AI and responsible deployment strategies to benefit from the latest advancements while maintaining safety, accuracy, and oversight. By directly applying concepts through hands-on labs and peer discussions, you will gain practical experience putting AI into production.
What's included
7 videos4 readings1 assignment1 ungraded lab
Offered by
Recommended if you're interested in Machine Learning
Duke University
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DeepLearning.AI
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