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Create a Text Generation Web App with 100% Python (NLP)


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Create a Text Generation Web App with 100% Python (NLP) Harness GPT-Neo -- a natural language processing (NLP) text generation model. Demonstrate it with a 100% Python web app

What you'll learn

  • How to implement state-of-the-art text generation AI models
  • Background information about GPT-Neo, a state-of-the-art text generation NLP model
  • How to use Happy Transformer -- a Python library for implementing NLP Transformer models
  • How to train/implement GPT-2
  • How to implement different text generation algorithms
  • How to fetch data using Hugging Face's Datasets library
  • How to train GPT-Neo using Happy Transformer
  • How to create a web app with 100% Python using Anvil
  • How to host a Transformer model on Paperspace


  • A solid understanding of basic Python syntax
  • A Google account (for Google Colab)


GPT-3 is a state-of-the-art text generation natural language processing (NLP) model created by OpenAI. You can use it to generate text that resembles text generated by a human.

This course will cover how to create a web app that uses an open-source version of GPT-3 called GPT-Neo with 100% Python. That’s right, no HTML, Javascript, CSS or any other programming language is required. Just 100% Python!

You will learn how to:

  • Implement GPT-Neo (and GPT-2) with Happy Transformer
  • Train GPT-Neo to generate unique text for a specific domain
  • Create a web app using 100% Python with Anvil!
  • Host your language model using Google Colab and Paperspace


NONE!!! All of the tools we use in this tutorial are web-based. They include Google Colab, Anvil and Paperspace. So regardless of if you’re on Mac, Windows or Linux, you will not have to worry about downloading any software.


  • Model: GPT-Neo -- an open-source version of GPT-3 created by Eleuther AI
  • Framework: Happy Transformer -- an open-source Python package that allows us to implement and train GPT-Neo with just a few lines of code
  • Web technologies: Anvil -- a website that allows us to develop web app using Python
  • Backend technologies: We’ll cover how to use both Google Colab and Paperspace to host the model. Anvil automatically covers hosting the web app.

About the instructor:

My name is Eric Fillion, and I’m from Canada. I’m on a mission to make state-of-the-art advances in the field of NLP through creating open-source tools and by creating educational content. In early 2020, I led a team that launched an open-source Python Package called Happy Transformer. Happy Transformer allows programmers to implement and train state-of-the-art Transformer models with just a few lines of code. Since its release, it has won awards and has been downloaded over 13k times.

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