Generative AI has moved from research labs into everyday applications. With the rise of large language models (LLMs), developers now have the tools to build chatbots, translators, summarizers, and intelligent assistants—all with Python.

Python for Generative AI & LLMs is a hands-on guide that takes you step by step through installing, running, fine-tuning, and deploying LLMs using Hugging Face Transformers and the latest Python libraries. Written for beginner to intermediate Python developers, this book focuses on practical skills, not heavy theory.

Inside you will learn how to:

Install Python, Jupyter, Hugging Face Transformers, and Datasets libraries
Understand tokens, tokenization, and how models process text
Work with pretrained models like GPT, LLaMA, and Falcon
Generate text, summaries, translations, and answers with a few lines of code
Fine-tune models for custom datasets and tasks
Build applications such as chatbots, semantic search, and code generators
Deploy your models with FastAPI and manage inference costs
Address challenges around token limits, bias, and responsible AI use

Every chapter introduces a concept, then follows with working Python code examples and outputs in plain text or tables. No plots or charts are required, making the material accessible and easy to follow.

Whether you are a developer entering the AI field, a student exploring NLP, or a professional looking to integrate AI into applications, this book will give you the skills to confidently build and deploy your own Generative AI systems.

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