Llm
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Large Language Models Llm And Api S
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Author : Anand Vemula
language : en
Publisher: Anand Vemula
Release Date :
Large Language Models Llm And Api S 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.
The Large Language Models API represents a transformative advancement in natural language processing (NLP), offering developers unparalleled access to state-of-the-art language models such as GPT-3. This API serves as a gateway to immense computational power and linguistic capabilities, empowering applications across diverse domains. At its core, the API provides seamless integration with existing software systems, enabling developers to harness the power of large language models without the complexities of model training and infrastructure management. By simply sending text inputs to the API, developers can receive rich, context-aware responses, opening new avenues for innovation in human-computer interaction. The API's capabilities span a wide range of tasks, including text generation, summarization, translation, sentiment analysis, and more. Whether automating content creation, enhancing customer service experiences, or powering virtual assistants, the API offers versatile solutions tailored to various use cases. Key features of the Large Language Models API include robust performance, scalability, and reliability. With access to vast amounts of training data and sophisticated neural network architectures, the API consistently delivers high-quality results across different languages and domains. Additionally, its scalable infrastructure ensures smooth operation even under heavy workloads, making it suitable for applications of any scale. Ethical considerations are paramount in AI development, and the API prioritizes responsible usage through features such as content moderation and bias detection. Developers can leverage these tools to mitigate the risks of misinformation, bias, and privacy violations, fostering trust and integrity in their applications. The API's documentation and developer resources provide comprehensive guidance for integration and usage, catering to developers of all skill levels. Additionally, community support and online forums offer opportunities for collaboration and knowledge sharing, driving innovation and collective learning. As the field of NLP continues to evolve, the Large Language Models API remains at the forefront of innovation, with ongoing updates and improvements to meet the evolving needs of developers and users alike. By leveraging the API's capabilities responsibly and creatively, developers can unlock new possibilities and redefine the boundaries of human-computer interaction.
Llm Design Patterns
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Author : Ken Huang
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-05-30
Llm Design Patterns written by Ken Huang 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 2025-05-30 with Computers categories.
Explore reusable design patterns, including data-centric approaches, model development, model fine-tuning, and RAG for LLM application development and advanced prompting techniques Key Features Learn comprehensive LLM development, including data prep, training pipelines, and optimization Explore advanced prompting techniques, such as chain-of-thought, tree-of-thought, RAG, and AI agents Implement evaluation metrics, interpretability, and bias detection for fair, reliable models Print or Kindle purchase includes a free PDF eBook Book DescriptionThis practical guide for AI professionals enables you to build on the power of design patterns to develop robust, scalable, and efficient large language models (LLMs). Written by a global AI expert and popular author driving standards and innovation in Generative AI, security, and strategy, this book covers the end-to-end lifecycle of LLM development and introduces reusable architectural and engineering solutions to common challenges in data handling, model training, evaluation, and deployment. You’ll learn to clean, augment, and annotate large-scale datasets, architect modular training pipelines, and optimize models using hyperparameter tuning, pruning, and quantization. The chapters help you explore regularization, checkpointing, fine-tuning, and advanced prompting methods, such as reason-and-act, as well as implement reflection, multi-step reasoning, and tool use for intelligent task completion. The book also highlights Retrieval-Augmented Generation (RAG), graph-based retrieval, interpretability, fairness, and RLHF, culminating in the creation of agentic LLM systems. By the end of this book, you’ll be equipped with the knowledge and tools to build next-generation LLMs that are adaptable, efficient, safe, and aligned with human values. What you will learn Implement efficient data prep techniques, including cleaning and augmentation Design scalable training pipelines with tuning, regularization, and checkpointing Optimize LLMs via pruning, quantization, and fine-tuning Evaluate models with metrics, cross-validation, and interpretability Understand fairness and detect bias in outputs Develop RLHF strategies to build secure, agentic AI systems Who this book is for This book is essential for AI engineers, architects, data scientists, and software engineers responsible for developing and deploying AI systems powered by large language models. A basic understanding of machine learning concepts and experience in Python programming is a must.
The Llm Advantage How To Unlock The Power Of Language Models For Business Success
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Author : Asish Dash
language : en
Publisher: Grazing Minds Publishing
Release Date : 2023-11-10
The Llm Advantage How To Unlock The Power Of Language Models For Business Success written by Asish Dash and has been published by Grazing Minds Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-11-10 with Business & Economics categories.
"The LLM Advantage: How to Harness the Power of Language, Logic, and Math Models for Your Business Success" is a comprehensive guide for individuals navigating the dynamic landscape of 21st-century business. Authored by Asish Dash, an experienced investor and entrepreneur with over a decade in technology startups, this book delves into the transformative realm of artificial intelligence, natural language processing, and data science. From ideation to execution to optimization, readers will explore the crucial role of Language, Logic, and Math Models (LLMs) in generating ideas, validating assumptions, building products, attracting customers, and improving overall business performance. Through real-world examples featuring prominent LLMs like GPT-3, BERT, and OpenAI Codex, the book illustrates how these models can interact with and understand natural language. It also examines the profound impact of LLMs on diverse business aspects, including product development, marketing, customer service, operations, strategy, and management. With insights from both successful and unsuccessful entrepreneurs, readers will gain valuable perspectives on navigating the opportunities and challenges posed by LLMs. The book provides a roadmap for developing the mindset, skills, and attributes of an LLM entrepreneur, offering practical tips, tools, and case studies for leveraging LLMs in business projects. Additionally, it addresses the ethical, legal, and technical considerations inherent in LLM entrepreneurship, guiding readers on best practices and risk mitigation. Closing with a forward-looking exploration of untapped potentials and emerging trends in LLM entrepreneurship, the book equips readers to discover new markets, industries, and innovations. The concluding chapter summarizes key takeaways, providing encouragement, inspiration, and resources for further exploration.
Generative Ai With Local Llm
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Author : Timur Isachenko
language : en
Publisher: Timur Isachenko
Release Date : 2024-10-04
Generative Ai With Local Llm written by Timur Isachenko and has been published by Timur Isachenko this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-10-04 with Computers categories.
A comprehensive roadmap for building AI-Driven applications with local LLMs
Enhancing Llm Performance
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Author : Peyman Passban
language : en
Publisher: Springer Nature
Release Date : 2025-07-04
Enhancing Llm Performance written by Peyman Passban and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-04 with Mathematics categories.
This book is a pioneering exploration of the state-of-the-art techniques that drive large language models (LLMs) toward greater efficiency and scalability. Edited by three distinguished experts—Peyman Passban, Mehdi Rezagholizadeh, and Andy Way—this book presents practical solutions to the growing challenges of training and deploying these massive models. With their combined experience across academia, research, and industry, the authors provide insights into the tools and strategies required to improve LLM performance while reducing computational demands. This book is more than just a technical guide; it bridges the gap between research and real-world applications. Each chapter presents cutting-edge advancements in inference optimization, model architecture, and fine-tuning techniques, all designed to enhance the usability of LLMs in diverse sectors. Readers will find extensive discussions on the practical aspects of implementing and deploying LLMs in real-world scenarios. The book serves as a comprehensive resource for researchers and industry professionals, offering a balanced blend of in-depth technical insights and practical, hands-on guidance. It is a go-to reference book for students, researchers in computer science and relevant sub-branches, including machine learning, computational linguistics, and more.
Llm Engineer S Handbook
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Author : Paul Iusztin
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-10-22
Llm Engineer S Handbook written by Paul Iusztin 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 2024-10-22 with Computers categories.
Step into the world of LLMs with this practical guide that takes you from the fundamentals to deploying advanced applications using LLMOps best practices Key Features Build and refine LLMs step by step, covering data preparation, RAG, and fine-tuning Learn essential skills for deploying and monitoring LLMs, ensuring optimal performance in production Utilize preference alignment, evaluation, and inference optimization to enhance performance and adaptability of your LLM applications Book DescriptionArtificial intelligence has undergone rapid advancements, and Large Language Models (LLMs) are at the forefront of this revolution. This LLM book offers insights into designing, training, and deploying LLMs in real-world scenarios by leveraging MLOps best practices. The guide walks you through building an LLM-powered twin that’s cost-effective, scalable, and modular. It moves beyond isolated Jupyter notebooks, focusing on how to build production-grade end-to-end LLM systems. Throughout this book, you will learn data engineering, supervised fine-tuning, and deployment. The hands-on approach to building the LLM Twin use case will help you implement MLOps components in your own projects. You will also explore cutting-edge advancements in the field, including inference optimization, preference alignment, and real-time data processing, making this a vital resource for those looking to apply LLMs in their projects. By the end of this book, you will be proficient in deploying LLMs that solve practical problems while maintaining low-latency and high-availability inference capabilities. Whether you are new to artificial intelligence or an experienced practitioner, this book delivers guidance and practical techniques that will deepen your understanding of LLMs and sharpen your ability to implement them effectively.What you will learn Implement robust data pipelines and manage LLM training cycles Create your own LLM and refine it with the help of hands-on examples Get started with LLMOps by diving into core MLOps principles such as orchestrators and prompt monitoring Perform supervised fine-tuning and LLM evaluation Deploy end-to-end LLM solutions using AWS and other tools Design scalable and modularLLM systems Learn about RAG applications by building a feature and inference pipeline Who this book is for This book is for AI engineers, NLP professionals, and LLM engineers looking to deepen their understanding of LLMs. Basic knowledge of LLMs and the Gen AI landscape, Python and AWS is recommended. Whether you are new to AI or looking to enhance your skills, this book provides comprehensive guidance on implementing LLMs in real-world scenarios
Building Llm Powered Applications
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Author : Valentina Alto
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-05-22
Building Llm Powered Applications written by Valentina Alto 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 2024-05-22 with Computers categories.
Get hands-on with GPT 3.5, GPT 4, LangChain, Llama 2, Falcon LLM and more, to build LLM-powered sophisticated AI applications Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Embed LLMs into real-world applications Use LangChain to orchestrate LLMs and their components within applications Grasp basic and advanced techniques of prompt engineering Book DescriptionBuilding LLM Powered Applications delves into the fundamental concepts, cutting-edge technologies, and practical applications that LLMs offer, ultimately paving the way for the emergence of large foundation models (LFMs) that extend the boundaries of AI capabilities. The book begins with an in-depth introduction to LLMs. We then explore various mainstream architectural frameworks, including both proprietary models (GPT 3.5/4) and open-source models (Falcon LLM), and analyze their unique strengths and differences. Moving ahead, with a focus on the Python-based, lightweight framework called LangChain, we guide you through the process of creating intelligent agents capable of retrieving information from unstructured data and engaging with structured data using LLMs and powerful toolkits. Furthermore, the book ventures into the realm of LFMs, which transcend language modeling to encompass various AI tasks and modalities, such as vision and audio. Whether you are a seasoned AI expert or a newcomer to the field, this book is your roadmap to unlock the full potential of LLMs and forge a new era of intelligent machines.What you will learn Explore the core components of LLM architecture, including encoder-decoder blocks and embeddings Understand the unique features of LLMs like GPT-3.5/4, Llama 2, and Falcon LLM Use AI orchestrators like LangChain, with Streamlit for the frontend Get familiar with LLM components such as memory, prompts, and tools Learn how to use non-parametric knowledge and vector databases Understand the implications of LFMs for AI research and industry applications Customize your LLMs with fine tuning Learn about the ethical implications of LLM-powered applications Who this book is for Software engineers and data scientists who want hands-on guidance for applying LLMs to build applications. The book will also appeal to technical leaders, students, and researchers interested in applied LLM topics. We don’t assume previous experience with LLM specifically. But readers should have core ML/software engineering fundamentals to understand and apply the content.
Beyond The Basics Supercharging Llm Reasoning And Coding
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Author : Aarthi Anbalagan
language : en
Publisher: Libertatem Media Private Limited
Release Date : 2024-08-12
Beyond The Basics Supercharging Llm Reasoning And Coding written by Aarthi Anbalagan and has been published by Libertatem Media Private Limited this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-08-12 with Business & Economics categories.
Large Language Models (LLMs) are revolutionizing how we interact with artificial intelligence, pushing the boundaries of reasoning, coding, and data-driven innovation. Beyond the Basics: Supercharging LLM Reasoning and Coding offers an in-depth exploration into optimizing these powerful tools for real-world applications. This book equips IT professionals, AI specialists, and senior executives with the knowledge to enhance LLM performance through high-quality data, supervised fine-tuning, and advanced techniques in reasoning and coding. It delves into essential topics such as leveraging proprietary data for strategic advantages, implementing robust fine-tuning frameworks, and overcoming common challenges in model deployment. From refining reasoning capabilities with advanced algorithms to boosting coding competency through targeted training, the book provides actionable insights and step-by-step methodologies. Readers will explore best practices for data collection, ethical considerations in AI deployment, and strategies for scaling LLM applications to meet industry-specific needs. Through real-world case studies and future-focused discussions, the book highlights emerging trends like multi-modal LLMs, real-time monitoring, and AI-driven decision-making. It also addresses key challenges such as data bias, scalability, and regulatory compliance, offering practical solutions for ethical and effective AI implementation. Whether you ' re leading AI initiatives or looking to deepen your expertise in LLMs, Beyond the Basics serves as an indispensable guide to harnessing the transformative power of artificial intelligence in today ’ s competitive landscape.
Mastering Llm Applications With Langchain And Hugging Face
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Author : Hunaidkhan Pathan
language : en
Publisher: BPB Publications
Release Date : 2024-09-21
Mastering Llm Applications With Langchain And Hugging Face written by Hunaidkhan Pathan and has been published by BPB Publications this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-21 with Computers categories.
DESCRIPTION The book is all about the basics of NLP, generative AI, and their specific component LLM. In this book, we have provided conceptual knowledge about different terminologies and concepts of NLP and NLG with practical hands-on. This comprehensive book offers a deep dive into the world of NLP and LLMs. Starting with the fundamentals of Python programming and code editors, the book gradually introduces NLP concepts, including text preprocessing, word embeddings, and transformer architectures. You will explore the architecture and capabilities of popular models like GPT-3 and BERT. The book also covers practical aspects of LLM usage for RAG applications using frameworks like LangChain and Hugging Face and deploying them in real world applications. With a focus on both theoretical knowledge and hands-on experience, this book is ideal for anyone looking to master the art of NLP and LLMs. The book also contains AWS Cloud deployment, which will help readers step into the world of cloud computing. As the book contains both theoretical and practical approaches, it will help the readers to gain confidence in the deployment of LLMs for any use cases, as well as get acquainted with the required generative AI knowledge to crack the interviews. KEY FEATURES ● Covers Python basics, NLP concepts, and terminologies, including LLM and RAG concepts. ● Provides exposure to LangChain, Hugging Face ecosystem, and chatbot creation using custom data. ● Guides on integrating chatbots with real-time applications and deploying them on AWS Cloud. WHAT YOU WILL LEARN ● Basics of Python, which contains Python concepts, installation, and code editors. ● Foundation of NLP and generative AI concepts and different terminologies being used in NLP and generative AI domain. ● LLMs and their importance in the cutting edge of AI. ● Creating chatbots using custom data using open source LLMs without spending a single penny. ● Integration of chatbots with real-world applications like Telegram. WHO THIS BOOK IS FOR This book is ideal for beginners and freshers entering the AI or ML field, as well as those at an intermediate level looking to deepen their understanding of generative AI, LLMs, and cloud deployment. TABLE OF CONTENTS 1. Introduction to Python and Code Editors 2. Installation of Python, Required Packages, and Code Editors 3. Ways to Run Python Scripts 4. Introduction to NLP and its Concepts 5. Introduction to Large Language Models 6. Introduction of LangChain, Usage and Importance 7. Introduction of Hugging Face, its Usage and Importance 8. Creating Chatbots Using Custom Data with LangChain and Hugging Face Hub 9. Hyperparameter Tuning and Fine Tuning Pre-Trained Models 10. Integrating LLMs into Real-World Applications–Case Studies 11. Deploying LLMs in Cloud Environments for Scalability 12. Future Directions: Advances in LLMs and Beyond Appendix A: Useful Tips for Efficient LLM Experimentation Appendix B: Resources and References
Langchain Applications In Modern Llm Development
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Author : William Smith
language : en
Publisher: HiTeX Press
Release Date : 2025-07-24
Langchain Applications In Modern Llm Development written by William Smith and has been published by HiTeX Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-24 with Computers categories.
"LangChain Applications in Modern LLM Development" "LangChain Applications in Modern LLM Development" serves as the definitive guide to deploying, scaling, and optimizing Large Language Model (LLM) applications with the powerful LangChain framework. Beginning with an insightful exploration of the historical evolution of LLMs and the motivating philosophy behind LangChain, the book positions this framework at the forefront of contemporary AI tooling. Detailed comparisons showcase LangChain's unique modularity, broad ecosystem integrations, and extensibility, setting the stage for both newcomers and advanced practitioners to appreciate its architectural strengths. Through clear explanations of foundational concepts such as chains, prompt management, and memory handling, the book equips readers to design and orchestrate robust, context-aware LLM workflows. Advanced chapters delve deep into data integration, retrieval augmented generation, agent-driven reasoning, tool management, and multi-agent orchestration. Security, compliance, and observability are treated as first-class concerns, with comprehensive guidance on safeguarding workflows, detecting threats, and ensuring transparency across deployments. Readers are also introduced to proven strategies for quality assurance and continuous evaluation, ensuring lasting reliability in production environments. Closing with real-world case studies across diverse domains—including enterprise knowledge systems, document automation, research assistants, and regulated industries—the book illuminates the transformative power of LangChain in modern AI applications. Forward-looking chapters examine emerging trends, multi-framework interoperability, sustainability, and the evolving LangChain community, making this text an indispensable resource for anyone seeking to harness the full potential of LLM technologies in both current and future contexts.