Book Image

Mastering PyTorch - Second Edition

By : Ashish Ranjan Jha
4 (1)
Book Image

Mastering PyTorch - Second Edition

4 (1)
By: Ashish Ranjan Jha

Overview of this book

PyTorch is making it easier than ever before for anyone to build deep learning applications. This PyTorch deep learning book will help you uncover expert techniques to get the most out of your data and build complex neural network models. You’ll build convolutional neural networks for image classification and recurrent neural networks and transformers for sentiment analysis. As you advance, you'll apply deep learning across different domains, such as music, text, and image generation, using generative models, including diffusion models. You'll not only build and train your own deep reinforcement learning models in PyTorch but also learn to optimize model training using multiple CPUs, GPUs, and mixed-precision training. You’ll deploy PyTorch models to production, including mobile devices. Finally, you’ll discover the PyTorch ecosystem and its rich set of libraries. These libraries will add another set of tools to your deep learning toolbelt, teaching you how to use fastai to prototype models and PyTorch Lightning to train models. You’ll discover libraries for AutoML and explainable AI (XAI), create recommendation systems, and build language and vision transformers with Hugging Face. By the end of this book, you'll be able to perform complex deep learning tasks using PyTorch to build smart artificial intelligence models.
Table of Contents (21 chapters)
20
Index

PyTorch and Hugging Face

We learned about parts of Hugging Face in Chapter 7, Music and Text Generation with PyTorch, as well as Chapter 10, Text-to-Image Generation. Hugging Face is an open-source platform and community-driven library that provides a comprehensive suite of AI tools, pre-trained models, and a collaborative ecosystem for developing and sharing state-of-the-art models. It has become one of the foundational platforms in the current AI landscape. We dedicate this chapter to learning more about Hugging Face and how PyTorch users can benefit from Hugging Face in researching, training, evaluating, optimizing, and deploying deep learning models.

By the end of this chapter, you will be able to use Hugging Face in your deep learning projects. You will be able to use pre-trained models from the Hugging Face Hub, use the Transformers library with PyTorch, speed up model training using Accelerate, and optimize your trained PyTorch models for deployment using Optimum.

This...