Using Transformers Locally
A simple guide to using transformer models on your machine!
Start Learning
A simple guide to using transformer models on your machine!
Start Learning
Welcome to this guide on learning how to use transformer models locally. This guide will walk you through the fundamental concepts, setup, and practical applications of transformers in natural language processing (NLP).
This chapter introduces the basics of transformer models and provides an overview of their applications in NLP.
Chapter 1This chapter covers text classification tasks using transformer models, demonstrating various NLP use cases.
Chapter 2This chapter provides a practical example of using transformers to detect hate speech in Arabic text.
Chapter 3Transformer Models are often seen as black boxes. Here we visualize the attention mask to see the relations a model makes.
Chapter 4aAfter visualizing the data in Part 1, we now extract the weights from a GPT model in Part 2, so we can learn how it makes its predictions.
Chapter 4bHere we explore the Mamba model and compare it to an 8B transformer model.
Chapter 5In this project I develop a pipeline to help doctors diagnose autism by simply reading their notes.
Chapter 6Here we use Stable Diffusion to convert text to images. Have a crazy idea? Make it into a picture in seconds!
Chapter 7In this project we convert images to text. Since we turned the image to text, we may as well add TTS as well!
Chapter 8Here are some additional resources to help you deepen your understanding of transformer models: