Unleash the full potential of transformers with this comprehensive guide covering architecture, capabilities, risks, and practical implementations on OpenAI, Google Vertex AI, and Hugging Face Key Features Master NLP and vision transformers, from the architecture to fine-tuning and implementation Combine generative AI tools, such as GPT-4, LangChain, and Stable Diffusion, to create automated generative ideation pipelines Mitigate LLM risks, such as hallucinations, using moderation models and knowledge bases Book DescriptionTransformers for Natural Language Processing and Computer Vision, Third Edition, is your gateway to the innovative world of Natural Language Processing (NLP) and Computer Vision (CV). This comprehensive guide examines the realm of Large Language Models (LLMs), including Generative AI and their transformative impact on NLP and CV. The book guides you through the Original Transformer and self-attention to the latest foundation models, including generative AI. Glimpse into the future with the functional artificial general intelligence (AGI) capabilities of GPT-4 and AI agent replication. Dive into generative vision transformers, creating new images, learning about different architectures, and building applications, such as image and video-to-text classifiers. Using your newly acquired knowledge of NLP and vision transformers, you'll go further by creating automating generative AI ideation pipelines. As well as learning about cutting-edge transformers, you'll discover the risks of these models, from hallucinations and memorization to privacy and cybersecurity. You'll mitigate risks using moderation models with rule bases and knowledge bases. This book equips you with the skills to take your LLM and generative AI endeavors to new heights. You'll gain a profound understanding of the latest trends in NLP, CV, and foundation models.What you will learn Master the art of fine-tuning models and engineering effective prompts Tackle examples of LLM risks by delving into strategies to mitigate them Learn about the potential functional AGI capabilities of foundation models Visualize transformer model activity for deeper insights using BertViz, LIME, and SHAP Create and implement cross-platform chained models, such as HuggingGPT Skyrocket your productivity with an automated generative ideation process Go in-depth into vision transformers with CLIP, DALL-E 2, DALL-E 3, and GPT-4V Who this book is forThis book is ideal for NLP and CV engineers, software developers, data scientists, machine learning engineers, and technical leaders looking to advance their LLMs and generative AI skills or explore the latest trends in the field. Knowledge of Python and machine learning concepts is required to fully understand the use cases and code examples. However, with examples using LLM user interfaces, prompt engineering, and no-code model building, this book is great for anyone curious about the AI revolution.