Deep Learning NLP: Training GPT-2 from scratch

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stars
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Offered By
Coursera Project Network
In this Guided Project, you will:

Understand the history of GPT-2 and Transformer Architecture Basics

Learn the requirements for a custom training set

Learn how to use functions available in public repositories to fine-tune or train GPT-2 on custom data and generate text

Clock2 hours
BeginnerBeginner
CloudNo download needed
VideoSplit-screen video
Comment DotsEnglish
LaptopDesktop only

In this 1-hour long project-based course, we will explore Transformer-based Natural Language Processing. Specifically, we will be taking a look at re-training or fine-tuning GPT-2, which is an NLP machine learning model based on the Transformer architecture. We will cover the history of GPT-2 and it's development, cover basics about the Transformer architecture, learn what type of training data to use and how to collect it, and finally, perform the fine tuning process. In the final task, we will discuss use cases and what the future holds for Transformer-based NLP. I would encourage learners to do further research and experimentation with the GPT-2 model, as well as other NLP models! Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.

Skills you will develop

Artificial Intelligence (AI)TensorflowMachine LearningNatural Language Processing

Learn step-by-step

In a video that plays in a split-screen with your work area, your instructor will walk you through these steps:

  1. Introducing GPT-2

  2. Intro to Transformers

  3. Gathering a Dataset

  4. Training and Fine Tuning our Model

  5. Use Cases and the Future

How Guided Projects work

Your workspace is a cloud desktop right in your browser, no download required

In a split-screen video, your instructor guides you step-by-step

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