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

Demonstrate it with a 100% Python web app

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, jаvascript, 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 ing 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 ed over 13k s.

Requirements:

A basic understanding of Python

A google account -- for Google Colab

Python developers interested in AI and NLP




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