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Transformer architectures have become the unified foundation of modern AI — powering language models, computer vision systems, and multimodal applications that process text, images, and speech together. Ultimate Multimodal Transformer Models provides a comprehensive, hands-on guide to mastering every major Transformer variant, from foundational encoder-decoder architectures to cutting-edge vision-language models and production GenAI systems. You begin with the core building blocks of Transformer architecture and text data preparation, then progressively advance through encoder-only models, generative LLMs, RAG, Agentic workflows, and efficient fine-tuning using PEFT, LoRA, and QLoRA. The book then transitions into Vision Transformers, covering ViT, DETR, SAM, CLIP, and Flamingo, before bringing everything together in real-world multimodal applications combining text, vision, and speech using PyTorch and Hugging Face throughout. By the end of the book, you will be proficient to build, fine-tune, and deploy Transformer-based AI systems across text, vision, and multimodal domains with confidence, applying the right architecture and strategy for every real-world use case!
Dr. S. Mahesh Anand is an educator, corporate trainer, and AI consultant with more than 20 years of experience and expertise in these fields. He has trained over 50,000 learners, founded SCS-India, and led programs like "Learn AI with Anand." An award-winning expert, Dr. Anand continues to inspire through his teaching, research, and his book on AI fundamentals.
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