/transformers-the-definitive-guide

This is the official repository for the book Transformers - The Definitive Guide

Primary LanguageJupyter NotebookApache License 2.0Apache-2.0

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Transformers - The definitive Guide

This is the corresponding code for the book Transformers - The definitive Guide The book can be found here

TOC

  • Chapter 1 From First Principles to State-of-the-Art Transformers
  • Chapter 2 Transformers for Time Series
  • Chapter 3 Transformers for Vision Tasks
  • Chapter 4 Transformers for Image Generation
  • Chapter 5 Transformers for Video Generation
  • Chapter 6 Transformers for Audio Tasks
  • Chapter 7 Reinforcement Learning Transformers
  • Chapter 8 Transformers for Planing, Reasoning and Coding
  • Chapter 9 AI Agents for Complex Tasks
  • Chapter 10 Optimizing Transformer for Problem Solving
  • Chapter 11 Deploying transformer models
  • Chapter 12 Where to go next

Instructions and Navigation

All of the code is organized into folders. Each folder starts with CH followed by the chapter number. For example, CH01. The notebooks are then organized as follows: ch01_attention_mechanism_variations.ipynb, where ch01 indicates the chapter and attention_mechanism_variations what is done in the notebook.

Repo structure

├── LICENSE
├── README.md             <- The top-level README for developers using this project.
├── CH01                  <- Per chapter folder with Jupyter notebooks.
    ├── [name].ipynb      <- Jupyter notebooks with naming as mentioned above.
├── CH02                  <- Per chapter folder with Jupyter notebooks.
...                       <- Same structure for all chapters.
├── utils                 <- Custom classes and functions and utility functions.
├── resources             <- Some miscellaneous resources.

Virtual Envrionment

The provided bash script create_env.sh automates the process of creating a Python virtual environment using either conda or pipenv, installing the required packages from a requirements.txt file. To use the script run bash create_env.sh in your terminal on Microsoft Windows (with WSL), Apple macOS, or Linux operating systems.

NOTE: A virtual environment is not necessary for the notebooks in this repository, as they are designed to be run on a cloud service with GPU support. Therefore, the provided instructions for creating a virtual environment are more for reference and general guidance than a strict requirement.

Running the Notebooks

Every notebook contains buttons so that the notebook can be oppend and run on the chosen cloud service like this:

Open In Colab Gradient

Each notebook is connected with this Github repo, meaning by running a notebook, it will automatically clone the repo, so you can easily access all resources outside the notebook. Like customs functions and classes as well as utility functions to automatically install the requirements per chapter:

!git clone https://github.com/Nicolepcx/transformers-the-definitive-guide

current_path = %pwd
if '/transformers-the-definitive-guide' in current_path:
    new_path = current_path + '/utils'
else:
    new_path = current_path + '/transformers-the-definitive-guide/utils'
%cd $new_path

NOTE: You need to run the notebooks with a GPU.