Duke University

Open Source LLMOps Solutions

This course is part of Large Language Model Operations (LLMOps) Specialization

Taught in English

Some content may not be translated

Noah Gift
Alfredo Deza

Instructors: Noah Gift

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Course

Gain insight into a topic and learn the fundamentals

Beginner level

Recommended experience

35 hours (approximately)
Flexible schedule
Learn at your own pace

What you'll learn

  • Run local large language models

  • Fine-tune LLMs

  • Use open-source generative AI

Details to know

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Recently updated!

March 2024

Assessments

9 assignments

Course

Gain insight into a topic and learn the fundamentals

Beginner level

Recommended experience

35 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Large Language Model Operations (LLMOps) Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
  • Learn new concepts from industry experts
  • Gain a foundational understanding of a subject or tool
  • Develop job-relevant skills with hands-on projects
  • Earn a shareable career certificate
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There are 4 modules in this course

In this module, you will learn how to leverage pre-trained natural language processing models to build NLP applications. We will explore popular open source models like BERT. You will learn how to access these models using libraries like HuggingFace Transformers and use them for tasks like text classification, question answering, and text generation. A key skill will be using large language models to synthetically augment datasets. By feeding the model examples and extracting the text it generates, you can create more training data. Through hands-on exercises, you will build basic NLP pipelines in Python that use pre-trained models to perform tasks like sentiment analysis. By the end of the module, you'll have practical experience using state-of-the-art NLP techniques to create capable language applications.

What's included

20 videos10 readings3 assignments1 discussion prompt

In this module, you run language models locally. Keep data private. Avoid latency and fees. Use Mixtral model and llamafile.

What's included

8 videos11 readings3 assignments3 ungraded labs

In this module, you will use models in the browser with Transformers.js and ONNX. You will gain experience on porting models to the ONNX runtime and experience how to put them on the browser. You will also use the Cosmopolitan project to build a phrase generator that is easily portable on different systems.

What's included

7 videos5 readings2 assignments1 ungraded lab

In this module, you will focus on completing several external labs and hands-on examples that will allow you to feel comfortable running local LLMs, connect to them with APIs using Python as well as building solutions with the Rust programming language

What's included

7 readings1 assignment1 ungraded lab

Instructors

Noah Gift
Duke University
40 Courses119,053 learners

Offered by

Duke University

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