Create a Text Generation Web App with 100% Python (NLP)
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
Requirements
- A solid understanding of basic Python syntax
- A Google account (for Google Colab)
Description
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
Installations:
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.
Technologies:
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.
Requirements:
A basic understanding of Python
A google account -- for Google Colab
Who this course is for:
- Python developers interested in AI and NLP
Instructors
- 4.7 Instructor Rating
- 75 Reviews
- 479 Students
- 2 Courses
The primary goal of Vennify AI is to create high-quality educational material surrounding NLP. This educational content will focus on Transformer models, as we believe they are a key technology within NLP.
Vennify was founded by Eric Fillion, who is also the lead maintainer of an open source Python package called Happy Transformer
- 4.7 Instructor Rating
- 75 Reviews
- 479 Students
- 2 Courses
My name is Eric Fillion, and I am the founder of Vennify Inc.
In 2020, my team published an open-sourced python library called Happy Transformer, which allows programmers to implement state-of-the-art Natural Language Processing (NLP) Transformer models with just a few lines of code. This library has been downloaded over 13k times, has won awards, and is currently used by experts worldwide.