You're reading from Transformers for Natural Language Processing and Computer Vision - Third Edition

Product type Book

Published in Feb 2024

Publisher Packt

ISBN-13 9781805128724

Pages 728 pages

Edition 3rd Edition

Languages

Python

Concepts

Deep Learning

Author (1):

Denis Rothman

Table of Contents (24) Chapters

Preface

What Are Transformers?

Getting Started with the Architecture of the Transformer Model

Emergent vs Downstream Tasks: The Unseen Depths of Transformers

Advancements in Translations with Google Trax, Google Translate, and Gemini

Diving into Fine-Tuning through BERT

Pretraining a Transformer from Scratch through RoBERTa

The Generative AI Revolution with ChatGPT

Fine-Tuning OpenAI GPT Models

Shattering the Black Box with Interpretable Tools

Investigating the Role of Tokenizers in Shaping Transformer Models

Leveraging LLM Embeddings as an Alternative to Fine-Tuning

Toward Syntax-Free Semantic Role Labeling with ChatGPT and GPT-4

Summarization with T5 and ChatGPT

Exploring Cutting-Edge LLMs with Vertex AI and PaLM 2

Guarding the Giants: Mitigating Risks in Large Language Models

Beyond Text: Vision Transformers in the Dawn of Revolutionary AI

Transcending the Image-Text Boundary with Stable Diffusion

Hugging Face AutoTrain: Training Vision Models without Coding

On the Road to Functional AGI with HuggingGPT and its Peers

Beyond Human-Designed Prompts with Generative Ideation

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Index

Appendix: Answers to the Questions

Uploading the dataset

First, click on Upload Training File(s) as shown in Figure 18.2:

A close-up of a cloud Description automatically generated

Figure 18.2: Uploading the training dataset

The interface may evolve, but you will need to upload data. You will need to read the documentation on the Hugging Face platform carefully to prepare your data. The interface evolves constantly to follow the cutting-edge AI market. Choose your method but remain focused on the task: loading data.

You will need to follow Hugging Face’s procedures for data formatting: https://huggingface.co/docs/autotrain/image_classification.

Make sure to read the upgrades regularly. Again, it is worthwhile!

In this case, we are loading CIFAR-10 images as shown in the Figure 18.3 excerpt:

A collage of different images of airplanes and cars Description automatically generated

Figure 18.3: Excerpt of CIFAR-10 transportation images

The CIFAR-10 images in this chapter are from Learning Multiple Layers of Features from Tiny Images, Alex Krizhevsky, 2009:https://www.cs.toronto.edu/~kriz/learning-features-2009-TR...