000			02065 a2200241 4500
005			20251215142501.0
008			251212b |||||||| |||| 00| 0 eng d
020			_a9798868805141
082			_a006.35 MAR
100			_aMartra, Pere
245			_aLarge language models projects: apply and implement strategies for large language models
260			_aNew York: _bAddison-Wesley, _c2024.
300			_axx, 356p.: _bill.; pbk.: _c26 cm.
504			_aIncludes Index
520			_aThis book offers you a hands-on experience using models from OpenAI and the Hugging Face library. You will use various tools and work on small projects, gradually applying the new knowledge you gain. The book is divided into three parts. Part one covers techniques and libraries. Here, you'll explore different techniques through small examples, preparing to build projects in the next section. You'll learn to use common libraries in the world of Large Language Models. Topics and technologies covered include chatbots, code generation, OpenAI API, Hugging Face, vector databases, LangChain, fine tuning, PEFT fine tuning, soft prompt tuning, LoRA, QLoRA, evaluating models, and Direct Preference Optimization. Part two focuses on projects. You'll create projects, understanding design decisions. Each project may have more than one possible implementation, as there is often not just one good solution. You'll also explore LLMOps-related topics. Part three delves into enterprise solutions. Large Language Models are not a standalone solution; in large corporate environments, they are one piece of the puzzle. You'll explore how to structure solutions capable of transforming organizations with thousands of employees, highlighting the main role that Large Language Models play in these new solutions. https://link.springer.com/book/10.1007/979-8-8688-0515-8#overview
650			_aOpenAI Models
650			_aCode Generation
650			_aHugging Face Tools
650			_aHands-On Projects
650			_aChatbots
650			_aLLM Projects
942			_cTD _2ddc
999			_c63901 _d63901