Demystifying Large Language Models
DOWNLOAD
Download Demystifying Large Language Models PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Demystifying Large Language Models book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page
Demystifying Large Language Models
DOWNLOAD
Author : James Chen
language : en
Publisher: James Chen
Release Date : 2024-04-25
Demystifying Large Language Models written by James Chen and has been published by James Chen this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-25 with Computers categories.
This book is a comprehensive guide aiming to demystify the world of transformers -- the architecture that powers Large Language Models (LLMs) like GPT and BERT. From PyTorch basics and mathematical foundations to implementing a Transformer from scratch, you'll gain a deep understanding of the inner workings of these models. That's just the beginning. Get ready to dive into the realm of pre-training your own Transformer from scratch, unlocking the power of transfer learning to fine-tune LLMs for your specific use cases, exploring advanced techniques like PEFT (Prompting for Efficient Fine-Tuning) and LoRA (Low-Rank Adaptation) for fine-tuning, as well as RLHF (Reinforcement Learning with Human Feedback) for detoxifying LLMs to make them aligned with human values and ethical norms. Step into the deployment of LLMs, delivering these state-of-the-art language models into the real-world, whether integrating them into cloud platforms or optimizing them for edge devices, this section ensures you're equipped with the know-how to bring your AI solutions to life. Whether you're a seasoned AI practitioner, a data scientist, or a curious developer eager to advance your knowledge on the powerful LLMs, this book is your ultimate guide to mastering these cutting-edge models. By translating convoluted concepts into understandable explanations and offering a practical hands-on approach, this treasure trove of knowledge is invaluable to both aspiring beginners and seasoned professionals. Table of Contents 1. INTRODUCTION 1.1 What is AI, ML, DL, Generative AI and Large Language Model 1.2 Lifecycle of Large Language Models 1.3 Whom This Book Is For 1.4 How This Book Is Organized 1.5 Source Code and Resources 2. PYTORCH BASICS AND MATH FUNDAMENTALS 2.1 Tensor and Vector 2.2 Tensor and Matrix 2.3 Dot Product 2.4 Softmax 2.5 Cross Entropy 2.6 GPU Support 2.7 Linear Transformation 2.8 Embedding 2.9 Neural Network 2.10 Bigram and N-gram Models 2.11 Greedy, Random Sampling and Beam 2.12 Rank of Matrices 2.13 Singular Value Decomposition (SVD) 2.14 Conclusion 3. TRANSFORMER 3.1 Dataset and Tokenization 3.2 Embedding 3.3 Positional Encoding 3.4 Layer Normalization 3.5 Feed Forward 3.6 Scaled Dot-Product Attention 3.7 Mask 3.8 Multi-Head Attention 3.9 Encoder Layer and Encoder 3.10 Decoder Layer and Decoder 3.11 Transformer 3.12 Training 3.13 Inference 3.14 Conclusion 4. PRE-TRAINING 4.1 Machine Translation 4.2 Dataset and Tokenization 4.3 Load Data in Batch 4.4 Pre-Training nn.Transformer Model 4.5 Inference 4.6 Popular Large Language Models 4.7 Computational Resources 4.8 Prompt Engineering and In-context Learning (ICL) 4.9 Prompt Engineering on FLAN-T5 4.10 Pipelines 4.11 Conclusion 5. FINE-TUNING 5.1 Fine-Tuning 5.2 Parameter Efficient Fine-tuning (PEFT) 5.3 Low-Rank Adaptation (LoRA) 5.4 Adapter 5.5 Prompt Tuning 5.6 Evaluation 5.7 Reinforcement Learning 5.8 Reinforcement Learning Human Feedback (RLHF) 5.9 Implementation of RLHF 5.10 Conclusion 6. DEPLOYMENT OF LLMS 6.1 Challenges and Considerations 6.2 Pre-Deployment Optimization 6.3 Security and Privacy 6.4 Deployment Architectures 6.5 Scalability and Load Balancing 6.6 Compliance and Ethics Review 6.7 Model Versioning and Updates 6.8 LLM-Powered Applications 6.9 Vector Database 6.10 LangChain 6.11 Chatbot, Example of LLM-Powered Application 6.12 WebUI, Example of LLM-Power Application 6.13 Future Trends and Challenges 6.14 Conclusion REFERENCES ABOUT THE AUTHOR
Breaking The Language Barrier Demystifying Language Models With Openai
DOWNLOAD
Author : Rayan Wali
language : en
Publisher: Rayan Wali
Release Date : 2023-03-08
Breaking The Language Barrier Demystifying Language Models With Openai written by Rayan Wali and has been published by Rayan Wali this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-08 with Computers categories.
Breaking the Language Barrier: Demystifying Language Models with OpenAI is an informative guide that covers practical NLP use cases, from machine translation to vector search, in a clear and accessible manner. In addition to providing insights into the latest technology that powers ChatGPT and other OpenAI language models, including GPT-3 and DALL-E, this book also showcases how to use OpenAI on the cloud, specifically on Microsoft Azure, to create scalable and efficient solutions.
Demystifying Large Language Models A Comprehensive Guide
DOWNLOAD
Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :
Demystifying Large Language Models A Comprehensive Guide written by Anand Vemula and has been published by Anand Vemula this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Demystifying Large Language Models: A Comprehensive Guide" serves as an essential roadmap for navigating the complex terrain of cutting-edge language technologies. In this book, readers are taken on a journey into the heart of Large Language Models (LLMs), exploring their significance, mechanics, and real-world applications. The narrative begins by contextualizing LLMs within the broader landscape of artificial intelligence and natural language processing, offering a clear understanding of their evolution and the pivotal role they play in modern computational linguistics. Delving into the workings of LLMs, the book breaks down intricate concepts into digestible insights, ensuring accessibility for both technical and non-technical audiences. Readers are introduced to the underlying architectures and training methodologies that power LLMs, including Transformer models like GPT (Generative Pre-trained Transformer) series. Through illustrative examples and practical explanations, complex technical details are demystified, empowering readers to grasp the essence of how these models generate human-like text and responses. Beyond theoretical underpinnings, the book explores diverse applications of LLMs across industries and disciplines. From natural language understanding and generation to sentiment analysis and machine translation, readers gain valuable insights into how LLMs are revolutionizing tasks once deemed exclusive to human intelligence. Moreover, the book addresses critical considerations surrounding ethics, bias, and responsible deployment of LLMs in real-world scenarios. It prompts readers to reflect on the societal implications of these technologies and encourages a thoughtful approach towards their development and utilization. With its comprehensive coverage and accessible language, "Demystifying Large Language Models" equips readers with the knowledge and understanding needed to engage with LLMs confidently. Whether you're a researcher, industry professional, or curious enthusiast, this book offers invaluable insights into the present and future of language technology.
Demystifying Large Language Models With Examples
DOWNLOAD
Author : Anand Vemula
language : en
Publisher: Independently Published
Release Date : 2024-05-17
Demystifying Large Language Models With Examples written by Anand Vemula and has been published by Independently Published this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-17 with Computers categories.
Demystifying large language models (LLMs), this book explores their inner workings, showcases their applications, and ponders their future impact. Part 1: Unveiling the LLM Landscape unveils the secrets behind these AI marvels. You'll learn how LLMs, trained on massive datasets of text and code, can understand and generate human-like language. Different LLM architectures and the key players developing them are also explored, providing a solid foundation for understanding this rapidly evolving field. Part 2: LLMs in Action brings these models to life with a showcase of their capabilities. From creating poems and code to summarizing complex information and translating languages, LLMs are transforming how we interact with machines. The book delves into how LLMs power chatbots and virtual assistants, automate repetitive coding tasks, and even assist programmers with debugging. Part 3: The Future of LLMs tackles the challenges and ethical considerations surrounding LLMs. It emphasizes the importance of mitigating bias in their outputs and ensuring transparency in their decision-making. Security and privacy concerns are also addressed, highlighting the need for responsible development practices. Looking ahead, the book explores how LLMs will revolutionize various industries. Education, customer service, and marketing are just a few examples where LLMs hold the potential to personalize experiences and streamline processes. The impact on creative fields is also discussed, with LLMs potentially serving as tools for inspiration while human creativity remains paramount. The book concludes by emphasizing the potential of LLMs and the importance of responsible development. By understanding their capabilities and limitations, we can harness the power of LLMs to shape a better future. This future hinges on ensuring LLMs are unbiased, transparent, and used for positive societal impact.
Mastering Nlp From Foundations To Llms
DOWNLOAD
Author : Lior Gazit
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-04-26
Mastering Nlp From Foundations To Llms written by Lior Gazit and has been published by Packt Publishing Ltd this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-26 with Computers categories.
Enhance your NLP proficiency with modern frameworks like LangChain, explore mathematical foundations and code samples, and gain expert insights into current and future trends Key Features Learn how to build Python-driven solutions with a focus on NLP, LLMs, RAGs, and GPT Master embedding techniques and machine learning principles for real-world applications Understand the mathematical foundations of NLP and deep learning designs Purchase of the print or Kindle book includes a free PDF eBook Book DescriptionDo you want to master Natural Language Processing (NLP) but don’t know where to begin? This book will give you the right head start. Written by leaders in machine learning and NLP, Mastering NLP from Foundations to LLMs provides an in-depth introduction to techniques. Starting with the mathematical foundations of machine learning (ML), you’ll gradually progress to advanced NLP applications such as large language models (LLMs) and AI applications. You’ll get to grips with linear algebra, optimization, probability, and statistics, which are essential for understanding and implementing machine learning and NLP algorithms. You’ll also explore general machine learning techniques and find out how they relate to NLP. Next, you’ll learn how to preprocess text data, explore methods for cleaning and preparing text for analysis, and understand how to do text classification. You’ll get all of this and more along with complete Python code samples. By the end of the book, the advanced topics of LLMs’ theory, design, and applications will be discussed along with the future trends in NLP, which will feature expert opinions. You’ll also get to strengthen your practical skills by working on sample real-world NLP business problems and solutions.What you will learn Master the mathematical foundations of machine learning and NLP Implement advanced techniques for preprocessing text data and analysis Design ML-NLP systems in Python Model and classify text using traditional machine learning and deep learning methods Understand the theory and design of LLMs and their implementation for various applications in AI Explore NLP insights, trends, and expert opinions on its future direction and potential Who this book is for This book is for deep learning and machine learning researchers, NLP practitioners, ML/NLP educators, and STEM students. Professionals working with text data as part of their projects will also find plenty of useful information in this book. Beginner-level familiarity with machine learning and a basic working knowledge of Python will help you get the best out of this book.
Llm Architectures A Comprehensive Guide Bert Bart Xlnet
DOWNLOAD
Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :
Llm Architectures A Comprehensive Guide Bert Bart Xlnet written by Anand Vemula and has been published by Anand Vemula this book supported file pdf, txt, epub, kindle and other format this book has been release on with Computers categories.
Demystifying the Power of Large Language Models: A Guide for Everyone Large Language Models (LLMs) are revolutionizing the way we interact with machines and information. This comprehensive guide unveils the fascinating world of LLMs, guiding you from their fundamental concepts to their cutting-edge applications. Master the Basics: Explore the foundational architectures like Recurrent Neural Networks (RNNs) and Transformers that power LLMs. Gain a clear understanding of how these models process and understand language. Deep Dives into Pioneering Architectures: Delve into the specifics of BERT, BART, and XLNet, three groundbreaking LLM architectures. Learn about their unique pre-training techniques and how they tackle various natural language processing tasks. Unveiling the Champions: A Comparative Analysis: Discover how these leading LLM architectures stack up against each other. Explore performance benchmarks and uncover the strengths and weaknesses of each model to understand which one is best suited for your specific needs. Emerging Frontiers: Charting the Course for the Future: Explore the exciting trends shaping the future of LLMs. Learn about the quest for ever-larger models, the growing focus on training efficiency, and the development of specialized architectures for tasks like question answering and dialogue systems. This book is not just about technical details. It provides real-world case studies and use cases, showcasing how LLMs are transforming various industries, from content creation and customer service to healthcare and education. With clear explanations and a conversational tone, this guide is perfect for anyone who wants to understand the power of LLMs and their potential impact on our world. Whether you're a tech enthusiast, a student, or a professional curious about the future of AI, this book is your one-stop guide to demystifying Large Language Models.
Information Integration And Web Intelligence
DOWNLOAD
Author : Pari Delir Haghighi
language : en
Publisher: Springer Nature
Release Date : 2023-11-22
Information Integration And Web Intelligence written by Pari Delir Haghighi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-22 with Computers categories.
This book constitutes the refereed conference proceedings of the 25th International Conference on Information Integration and Web Intelligence, iiWAS 2023, organized in conjunction with the 21st International Conference on Advances in Mobile Computing and Multimedia Intelligence, MoMM2023, held in Denpasar, Bali, Indonesia, during December 4-6, 2023. The 24 full papers and 24 short papers presented in this book were carefully reviewed and selected from 96 submissions. The papers are divided into the following topical sections: business data and applications; data management; deep and machine Learning; generative AI; image data and knowledge graph; recommendation systems; similarity measure and metric; and topic and text matching.
Generative Ai For Business Leaders
DOWNLOAD
Author : I. Almeida
language : en
Publisher: Now Next Later AI
Release Date : 2023-12-03
Generative Ai For Business Leaders written by I. Almeida and has been published by Now Next Later AI this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-12-03 with Business & Economics categories.
2025 Edition. Business leaders must understand how to effectively leverage Generative AI within their companies in order to remain competitive. This book collection offers a fresh, timely viewpoint on this critical topic. Readers will gain foundational knowledge about AI and Generative algorithms while exploring both the potential benefits, risks and ethics involved. Guidance is provided on enhancing an organization's offerings, operating model and strategic direction while mitigating biases and negative consequences. The book collection lays out a comprehensive approach for businesses to successfully adopt and integrate Generative AI technologies. Common errors and challenges that companies face in this relatively new domain are highlighted, along with proven tactics to overcome them and achieve strong results. A comprehensive playbook to unlock the commercial potential of generative AI for managers, directors, executives, governance specialists, and any professionals interested in the intersection of business and emerging technologies. Book: Generative AI Transformation Blueprint Drawing on insights from AI-enabled business transformations in diverse sectors, it presents a validated strategic approach. This blueprint not only outlines best practices but also showcases pioneering use cases, integrating them into a cohesive framework for practical implementation. This scenario-based approach helps leaders understand where and how to apply the practices outlined. Spanning across areas from strategic alignment and talent development to ethical governance and sustaining a competitive edge amid relentless underlying progress, it delivers clarity for charting an optimal Generative AI roadmap. Book: Introduction to Large Language Models for Business Leaders: Responsible AI Strategy Beyond Fear and Hype Finalist for the 2023 HARVEY CHUTE Book Awards recognizing emerging talent and outstanding works in the genre of Business and Enterprise Non-Fiction. Explore the transformative potential of technologies like ChatGPT and Claude. These large language models (LLMs) promise to reshape how businesses operate. Aimed at non-technical business leaders, this guide offers a pragmatic approach to leveraging LLMs for tangible benefits, while ensuring ethical considerations aren't sidelined. LLMs can refine processes in marketing, software development, HR, R&D, customer service, and even legal operations. But it's essential to approach them with a balanced view. In this guide, you'll: - Learn about the rapid advancements of LLMs. - Understand complex concepts in simple terms. - Discover practical business applications. - Get strategies for smooth integration. - Assess potential impacts on your team. - Delve into the ethics of deploying LLMs. Book: Artificial Intelligence Fundamentals for Business Leaders: Up to Date With Generative AI The perfect guide to help non-technical business leaders understand the power of AI: Machine Learning, Neural Networks, and Data Management. Up to date with Generative AI. More Than a Book Collection By purchasing this series, you will also be granted free access to the AI Academy platform. There you can test your knowledge through end-of-chapter quizzes and engage in discussion. You will also receive free modules and 50% discount toward the enrollment in the self-paced course of the same name and enjoy video summary lessons, instructor-graded assignments, and live sessions. A course certificate will be awarded upon successful completion.
Developing Apps With Gpt 4 And Chatgpt
DOWNLOAD
Author : Olivier Caelen
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2023-08-29
Developing Apps With Gpt 4 And Chatgpt written by Olivier Caelen and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-08-29 with Computers categories.
This minibook is a comprehensive guide for Python developers who want to learn how to build applications with large language models. Authors Olivier Caelen and Marie-Alice Blete cover the main features and benefits of GPT-4 and ChatGPT and explain how they work. You'll also get a step-by-step guide for developing applications using the GPT-4 and ChatGPT Python library, including text generation, Q&A, and content summarization tools. Written in clear and concise language, Developing Apps with GPT-4 and ChatGPT includes easy-to-follow examples to help you understand and apply the concepts to your projects. Python code examples are available in a GitHub repository, and the book includes a glossary of key terms. Ready to harness the power of large language models in your applications? This book is a must. You'll learn: The fundamentals and benefits of ChatGPT and GPT-4 and how they work How to integrate these models into Python-based applications for NLP tasks How to develop applications using GPT-4 or ChatGPT APIs in Python for text generation, question answering, and content summarization, among other tasks Advanced GPT topics including prompt engineering, fine-tuning models for specific tasks, plug-ins, LangChain, and more
Build A Large Language Model From Scratch
DOWNLOAD
Author : Sebastian Raschka
language : en
Publisher: Simon and Schuster
Release Date : 2024-10-29
Build A Large Language Model From Scratch written by Sebastian Raschka and has been published by Simon and Schuster this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-29 with Computers categories.
Learn how to create, train, and tweak large language models (LLMs) by building one from the ground up! In Build a Large Language Model (from Scratch) bestselling author Sebastian Raschka guides you step by step through creating your own LLM. Each stage is explained with clear text, diagrams, and examples. You’ll go from the initial design and creation, to pretraining on a general corpus, and on to fine-tuning for specific tasks. Build a Large Language Model (from Scratch) teaches you how to: • Plan and code all the parts of an LLM • Prepare a dataset suitable for LLM training • Fine-tune LLMs for text classification and with your own data • Use human feedback to ensure your LLM follows instructions • Load pretrained weights into an LLM Build a Large Language Model (from Scratch) takes you inside the AI black box to tinker with the internal systems that power generative AI. As you work through each key stage of LLM creation, you’ll develop an in-depth understanding of how LLMs work, their limitations, and their customization methods. Your LLM can be developed on an ordinary laptop, and used as your own personal assistant. About the technology Physicist Richard P. Feynman reportedly said, “I don’t understand anything I can’t build.” Based on this same powerful principle, bestselling author Sebastian Raschka guides you step by step as you build a GPT-style LLM that you can run on your laptop. This is an engaging book that covers each stage of the process, from planning and coding to training and fine-tuning. About the book Build a Large Language Model (From Scratch) is a practical and eminently-satisfying hands-on journey into the foundations of generative AI. Without relying on any existing LLM libraries, you’ll code a base model, evolve it into a text classifier, and ultimately create a chatbot that can follow your conversational instructions. And you’ll really understand it because you built it yourself! What's inside • Plan and code an LLM comparable to GPT-2 • Load pretrained weights • Construct a complete training pipeline • Fine-tune your LLM for text classification • Develop LLMs that follow human instructions About the reader Readers need intermediate Python skills and some knowledge of machine learning. The LLM you create will run on any modern laptop and can optionally utilize GPUs. About the author Sebastian Raschka, PhD, is an LLM Research Engineer with over a decade of experience in artificial intelligence. His work spans industry and academia, including implementing LLM solutions as a senior engineer at Lightning AI and teaching as a statistics professor at the University of Wisconsin–Madison. Sebastian collaborates with Fortune 500 companies on AI solutions and serves on the Open Source Board at University of Wisconsin–Madison. He specializes in LLMs and the development of high-performance AI systems, with a deep focus on practical, code-driven implementations. He is the author of the bestselling books Machine Learning with PyTorch and Scikit-Learn, and Machine Learning Q and AI. The technical editor on this book was David Caswell. Table of Contents 1 Understanding large language models 2 Working with text data 3 Coding attention mechanisms 4 Implementing a GPT model from scratch to generate text 5 Pretraining on unlabeled data 6 Fine-tuning for classification 7 Fine-tuning to follow instructions A Introduction to PyTorch B References and further reading C Exercise solutions D Adding bells and whistles to the training loop E Parameter-efficient fine-tuning with LoRA