Generative Ai With Local Llm

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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

Hands On Generative Ai With Transformers And Diffusion Models

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Author : Omar Sanseviero
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-11-22

Hands On Generative Ai With Transformers And Diffusion Models written by Omar Sanseviero 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 2024-11-22 with Computers categories.

Learn to use generative AI techniques to create novel text, images, audio, and even music with this practical, hands-on book. Readers will understand how state-of-the-art generative models work, how to fine-tune and adapt them to their needs, and how to combine existing building blocks to create new models and creative applications in different domains. This go-to book introduces theoretical concepts followed by guided practical applications, with extensive code samples and easy-to-understand illustrations. You'll learn how to use open source libraries to utilize transformers and diffusion models, conduct code exploration, and study several existing projects to help guide your work. Build and customize models that can generate text and images Explore trade-offs between using a pretrained model and fine-tuning your own model Create and utilize models that can generate, edit, and modify images in any style Customize transformers and diffusion models for multiple creative purposes Train models that can reflect your own unique style

Generative Ai With Langchain

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Author : Ben Auffarth
language : en
Publisher: Packt Publishing Ltd
Release Date : 2023-12-22

Generative Ai With Langchain written by Ben Auffarth 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 2023-12-22 with Computers categories.

2024 Edition – Get to grips with the LangChain framework to develop production-ready applications, including agents and personal assistants. The 2024 edition features updated code examples and an improved GitHub repository. Get With Your Book: PDF Copy, AI Assistant, and Next-Gen Reader Free Key Features Learn how to leverage LangChain to work around LLMs’ inherent weaknesses Delve into LLMs with LangChain and explore their fundamentals, ethical dimensions, and application challenges Get better at using ChatGPT and GPT models, from heuristics and training to scalable deployment, empowering you to transform ideas into reality Book DescriptionChatGPT and the GPT models by OpenAI have brought about a revolution not only in how we write and research but also in how we can process information. This book discusses the functioning, capabilities, and limitations of LLMs underlying chat systems, including ChatGPT and Gemini. It demonstrates, in a series of practical examples, how to use the LangChain framework to build production-ready and responsive LLM applications for tasks ranging from customer support to software development assistance and data analysis – illustrating the expansive utility of LLMs in real-world applications. Unlock the full potential of LLMs within your projects as you navigate through guidance on fine-tuning, prompt engineering, and best practices for deployment and monitoring in production environments. Whether you're building creative writing tools, developing sophisticated chatbots, or crafting cutting-edge software development aids, this book will be your roadmap to mastering the transformative power of generative AI with confidence and creativity.What you will learn Create LLM apps with LangChain, like question-answering systems and chatbots Understand transformer models and attention mechanisms Automate data analysis and visualization using pandas and Python Grasp prompt engineering to improve performance Fine-tune LLMs and get to know the tools to unleash their power Deploy LLMs as a service with LangChain and apply evaluation strategies Privately interact with documents using open-source LLMs to prevent data leaks Who this book is for The book is for developers, researchers, and anyone interested in learning more about LangChain. Whether you are a beginner or an experienced developer, this book will serve as a valuable resource if you want to get the most out of LLMs using LangChain. Basic knowledge of Python is a prerequisite, while prior exposure to machine learning will help you follow along more easily.

Generative Ai With Python And Pytorch Second Edition

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Author : Joseph Babcock
language : en
Publisher: Packt Publishing Ltd
Release Date : 2025-03-28

Generative Ai With Python And Pytorch Second Edition written by Joseph Babcock 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 2025-03-28 with Computers categories.

Master GenAI techniques to create images and text using variational autoencoders (VAEs), generative adversarial networks (GANs), LSTMs, and large language models (LLMs) Key Features Implement real-world applications of LLMs and generative AI Fine-tune models with PEFT and LoRA to speed up training Expand your LLM toolbox with Retrieval Augmented Generation (RAG) techniques, LangChain, and LlamaIndex Purchase of the print or Kindle book includes a free eBook in PDF format Book Description Become an expert in Generative AI through immersive, hands-on projects that leverage today’s most powerful models for Natural Language Processing (NLP) and computer vision. Generative AI with Python and PyTorch is your end-to-end guide to creating advanced AI applications, made easy by Raghav Bali, a seasoned data scientist with multiple patents in AI, and Joseph Babcock, a PhD and machine learning expert. Through business-tested approaches, this book simplifies complex GenAI concepts, making learning both accessible and immediately applicable. From NLP to image generation, this second edition explores practical applications and the underlying theories that power these technologies. By integrating the latest advancements in LLMs, it prepares you to design and implement powerful AI systems that transform data into actionable intelligence. You’ll build your versatile LLM toolkit by gaining expertise in GPT-4, LangChain, RLHF, LoRA, RAG, and more. You’ll also explore deep learning techniques for image generation and apply styler transfer using GANs, before advancing to implement CLIP and diffusion models. Whether you’re generating dynamic content or developing complex AI-driven solutions, this book equips you with everything you need to harness the full transformative power of Python and AI. What will you learn Grasp the core concepts and capabilities of LLMs Craft effective prompts using chain-of-thought, ReAct, and prompt query language to guide LLMs toward your desired outputs Understand how attention and transformers have changed NLP Optimize your diffusion models by combining them with VAEs Build text generation pipelines based on LSTMs and LLMs Leverage the power of open-source LLMs, such as Llama and Mistral, for diverse applications Who this book is for This book is for data scientists, machine learning engineers, and software developers seeking practical skills in building generative AI systems. A basic understanding of math and statistics and experience with Python coding is required.

Building Generative Ai Agents

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Author : Tom Taulli
language : en
Publisher: Springer Nature
Release Date : 2025-06-15

Building Generative Ai Agents written by Tom Taulli and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-15 with Computers categories.

The dawn of AI agents is upon us. Tech visionaries like Bill Gates, Andrew Ng, and Vinod Khosla have highlighted the monumental potential of this powerful technology. This book will provide the knowledge and tools necessary to build generative AI agents using the most popular frameworks, such as AutoGen, LangChain, LangGraph, CrewAI, and Haystack. Recent breakthroughs in large language models have opened up unprecedented possibilities. After years of gradual progress in machine learning and deep learning, we are now witnessing novel approaches capable of understanding, reasoning, and generating content in ways that promise to revolutionize nearly every industry. This platform shift is as significant as the advent of mainframes, PCs, cloud computing, mobile technology, and social media. It’s why the world’s largest technology companies – like Microsoft, Apple, Google, and Meta – are making enormous investments in this category. While chatbots like ChatGPT, Claude, and Gemini have demonstrated remarkable potential, the years ahead will see the rise of generative AI agents capable of executing complex tasks on behalf of users. These agents already exhibit capabilities such as running test suites, searching the web for documentation, writing software, answering questions based on vast organized information, and performing intricate web-based tasks across multiple domains. They can autonomously investigate cybersecurity incidents and address complex customer support needs. By integrating skills, knowledge bases, planning frameworks, memory, and feedback loops, these systems can handle many tasks and improve over time. Building Generative AI Agents serves as a high-quality guide for developers to understand when and where AI agents can be useful, their advantages and disadvantages, and practical advice on designing, building, deploying, and monitoring them. What You Will Learn The foundational concepts, capabilities, and potential of AI agents. Recent innovations in large language models that have enabled the development of AI agents. How to build AI agents for launching a product, creating a financial plan, handling customer service, and using Retrieval Augmented Generation (RAG). Essential frameworks for building generative AI agents, including AutoGen, LangChain, LangGraph, CrewAI, and Haystack. Step-by-step guidance on designing, building, and deploying AI agents. Insights into the future of AI agents and their potential impact on various industries. Who This Book Is For Experienced software developers

Prompt Engineering For Generative Ai

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Author : James Phoenix
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2024-05-16

Prompt Engineering For Generative Ai written by James Phoenix 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 2024-05-16 with categories.

Large language models (LLMs) and diffusion models such as ChatGPT and Stable Diffusion have unprecedented potential. Because they have been trained on all the public text and images on the internet, they can make useful contributions to a wide variety of tasks. And with the barrier to entry greatly reduced today, practically any developer can harness LLMs and diffusion models to tackle problems previously unsuitable for automation. With this book, you'll gain a solid foundation in generative AI, including how to apply these models in practice. When first integrating LLMs and diffusion models into their workflows, most developers struggle to coax reliable enough results from them to use in automated systems. Authors James Phoenix and Mike Taylor show you how a set of principles called prompt engineering can enable you to work effectively with AI. Learn how to empower AI to work for you. This book explains: The structure of the interaction chain of your program's AI model and the fine-grained steps in between How AI model requests arise from transforming the application problem into a document completion problem in the model training domain The influence of LLM and diffusion model architecture—and how to best interact with it How these principles apply in practice in the domains of natural language processing, text and image generation, and code

Generative Ai For Effective Software Development

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Author : Anh Nguyen-Duc
language : en
Publisher: Springer Nature
Release Date : 2024-05-31

Generative Ai For Effective Software Development written by Anh Nguyen-Duc and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-05-31 with Computers categories.

This book provides a comprehensive, empirically grounded exploration of how Generative AI is reshaping the landscape of software development. It emphasizes the empirical evaluation of Generative AI tools in real-world scenarios, offering insights into their practical efficacy, limitations, and impact. By presenting case studies, surveys, and interviews from various software development contexts, the book offers a global perspective on the integration of Generative AI, highlighting how these advanced tools are adapted to and influence diverse cultural, organizational, and technological environments. This book is structured to provide a comprehensive understanding of Generative AI and its transformative impact on the field of software engineering. The book is divided into five parts, each focusing on different aspects of Generative AI in software development. As an introduction, Part 1 presents the fundamentals of Generative AI adoption. Part 2 is a collection of empirical studies and delves into the practical aspects of integrating Generative AI tools in software engineering, with a focus on patterns, methodologies, and comparative analyses. Next, Part 3 presents case studies that showcase the application and impact of Generative AI in various software development contexts. Part 4 then examines how Generative AI is reshaping software engineering processes, from collaboration and workflow to management and agile development. Finally, Part 5 looks towards the future, exploring emerging trends, future directions, and the role of education in the context of Generative AI. The book offers diverse perspectives as it compiles research and experiences from various countries and software development environments. It also offers non-technical discussions about Generative AI in management, teamwork, business and education. This way, it is intended for both researchers in software engineering and for professionals in industry who want to learn about the impactof Generative AI on software development.

Institutional Guide To Using Ai For Research

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Author : Xue Zhou
language : en
Publisher: Springer Nature
Release Date : 2025-07-21

Institutional Guide To Using Ai For Research written by Xue Zhou and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-21 with Education categories.

This book provides a comprehensive exploration of the integration of artificial intelligence (AI) into academic research, specifically tailored for higher education institutions and postgraduate research (PGR) students. It addresses the unique challenges and opportunities that these institutions and students encounter when incorporating AI into research. The work emphasises practical case studies, step-by-step guides on AI tools and techniques, ethical considerations in AI usage, and features contributions from experts across various disciplines. Following the introduction, the book delves into the specifics of how AI can enhance academic research such as literature review, data analysis and interpretation, and assistance in academic writing across different disciplines. The wide range of topics introduced in this book is supported by practical examples and guidance. This book also explores the landscape of current AI applications in research, the methodologies for effectively leveraging AI technologies, and the critical ethical dimensions of AI work. The importance of interdisciplinary collaboration in expanding the use of AI in research is covered in this book by drawing on expert insights to provide a rich, multifaceted understanding of the potential of AI in academia. The combination of topics in this book can empower PGR students to navigate the complexities of AI in their research. The book is a much-needed compilation prepared by leading scholars in the field of digital technology to help PGRs, as well as decision-makers, determine the best ways to integrate and use AI tools in research.

Ai For Everyday It

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Author : Chrissy LeMaire
language : en
Publisher: Simon and Schuster
Release Date : 2025-06-24

Ai For Everyday It written by Chrissy LeMaire 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 2025-06-24 with Computers categories.

Automate and accelerate your everyday IT tasks with instant solutions! What if you never had to write another after-incident report, piece of boilerplate code, or a performance review from scratch ever again? Use AI tools like ChatGPT, Claude, Gemini, and Copilot right, and you’ll take back hours of your time—and more! AI for Everyday IT reveals how you can automate dozens of your daily IT tasks with generative AI. In AI for Everyday IT you’ll learn how to: • Write effective prompts for common IT tasks • Optimize report generation, document handling, and workplace communication • Resolve IT conflicts and crises • Acquire new skills and upgrade your resume • AI for help desk, database administration and systems administration • Incorporate AI into DevOps processes and create AI-powered applications • Simplify time-consuming people management tasks In this hands-on guide, automation experts Chrissy LeMaire and Brandon Abshire show you how AI tools like ChatGPT have made their lives a million times easier, and how they can do the same for you. You’ll find proven strategies for using AI to improve help desk support, automate sysadmin and database tasks, aid with DevOps engineering, handle managing IT teams, and dozens more time-saving and quality-improving hacks. Foreword by Nitya Narasimhan. About the technology Have you lost days sifting through logs to find a latency issue? AI can do it in seconds! Need to update your documentation? Mere moments for AI. Are you writing scripts, designing data recovery strategies, and evaluating network designs? AI can handle it all—if you know how to use it. About the book AI for Everyday IT shows you exactly how AI can transform support desk operations, root cause analysis, disaster recovery planning—even writing professional emails when you’re too furious to be nice! This instantly-useful guide has time-saving techniques for all IT pros—from devs and DBAs to technical writers and product managers. Each relatable example is fully illustrated with the prompts and problem formulation strategies, along with interesting insights and anecdotes from authors Chrissy Lemaire and Brandon Abshire. What's inside • Document handling and workplace communication • Database administration and development • DevOps engineering and AI powered apps • People management and career planning About the reader Whether you’re working in operations, development, management, or security, you’ll love these productivity hacks for generative AI. No previous AI experience required. About the author Chrissy LeMaire is a dual Microsoft MVP and GitHub Star, the creator of dbatools, and author of the Manning book Learn dbatools in a Month of Lunches. Brandon Abshire has spent over twenty years in IT, including roles at a leading Fortune 500 semiconductor and telecommunications company and multiple top-ranked US hospital systems. Table of Contents Part 1 1 Artificial intelligence in IT 2 Chatbots: Tasks and tips 3 Basic intelligence 4 Prompt engineering and problem formulation 5 Prompts in action 6 Document handling 7 Emails and instant messaging in the workplace Part 2 8 IT support and service desk 9 Systems administration 10 Database administration and development Part 3 11 Code assistants and development tools 12 AI in DevOps engineering 13 Building AI-powered applications Part 4 14 Conflict resolution and crisis management 15 Management essentials 16 Management interventions 17 Career advancement A Local AI models: An accessible alternative B OpenAI GPT Actions

Building Data Driven Applications With Llamaindex

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Author : Andrei Gheorghiu
language : en
Publisher: Packt Publishing Ltd
Release Date : 2024-05-10

Building Data Driven Applications With Llamaindex written by Andrei Gheorghiu 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 2024-05-10 with Computers categories.

Solve real-world problems easily with artificial intelligence (AI) using the LlamaIndex data framework to enhance your LLM-based Python applications Key Features Examine text chunking effects on RAG workflows and understand security in RAG app development Discover chatbots and agents and learn how to build complex conversation engines Build as you learn by applying the knowledge you gain to a hands-on project Book DescriptionDiscover the immense potential of Generative AI and Large Language Models (LLMs) with this comprehensive guide. Learn to overcome LLM limitations, such as contextual memory constraints, prompt size issues, real-time data gaps, and occasional ‘hallucinations’. Follow practical examples to personalize and launch your LlamaIndex projects, mastering skills in ingesting, indexing, querying, and connecting dynamic knowledge bases. From fundamental LLM concepts to LlamaIndex deployment and customization, this book provides a holistic grasp of LlamaIndex's capabilities and applications. By the end, you'll be able to resolve LLM challenges and build interactive AI-driven applications using best practices in prompt engineering and troubleshooting Generative AI projects.What you will learn Understand the LlamaIndex ecosystem and common use cases Master techniques to ingest and parse data from various sources into LlamaIndex Discover how to create optimized indexes tailored to your use cases Understand how to query LlamaIndex effectively and interpret responses Build an end-to-end interactive web application with LlamaIndex, Python, and Streamlit Customize a LlamaIndex configuration based on your project needs Predict costs and deal with potential privacy issues Deploy LlamaIndex applications that others can use Who this book is for This book is for Python developers with basic knowledge of natural language processing (NLP) and LLMs looking to build interactive LLM applications. Experienced developers and conversational AI developers will also benefit from the advanced techniques covered in the book to fully unleash the capabilities of the framework.