000			02068nam a22002537a 4500
005			20260727164802.0
008			260727s2024 |||||||| |||| 00| 0 eng d
020			_a9781805128724
040			_cPK-LaUMT
082			_a006.35 _bROT-T
100	1		_aRothman, Denis _914304
245	1	0	_aTransformers for natural language processing and computer vision : _bexplore generative AI and large language models with Hugging Face, ChatGPT, GPT-4V, and DALL-E3 / _cDenis Rothman
250			_a3rd ed.
260			_aBirmingham : _bPackt Publishing, _c2024
300			_axxxii, 691 p.
490			_aExpert insight
500			_aIndex present
520			_a"Transformers for Natural Language Processing and Computer Vision, Third Edition, explores Large Language Model (LLM) architectures, applications, and various platforms (Hugging Face, OpenAI, and Google Vertex AI) used for Natural Language Processing (NLP) and Computer Vision (CV). The book guides you through different transformer architectures to the latest Foundation Models and Generative AI. You'll pretrain and fine-tune LLMs and work through different use cases, from summarization to implementing question-answering systems with embedding-based search techniques. You will also learn the risks of LLMs, from hallucinations and memorization to privacy, and how to mitigate such risks using moderation models with rule and knowledge bases. You'll implement Retrieval Augmented Generation (RAG) with LLMs to improve the accuracy of your models and gain greater control over LLM outputs. Dive into generative vision transformers and multimodal model architectures and build applications, such as image and video-to-text classifiers. Go further by combining different models and platforms and learning about AI agent replication. This book provides you with an understanding of transformer architectures, pretraining, fine-tuning, LLM use cases, and best practices"--Back cover
546			_aEng
650			_aMachine learning
650			_aDeep learning
650			_aArtificial intelligence
942			_cBK
999			_c141690 _d141690