Mastering Transformers for Practical NLP: A Hands on guide to BERT, GPT, T5, LLAMA, RAG, LORA and real world NLP applications using Hugging Face, Langchain and Open LLM frameworks
Mastering Transformers for Practical NLP: A Hands on guide to BERT, GPT, T5, LLAMA, RAG, LORA and real world NLP applications using Hugging Face, Langchain and Open LLM frameworks
Mastering Transformers for Practical NLP A Hands-On Guide to BERT, GPT, T5, LLaMA, RAG, LoRA, and Real-World NLP Applications Using Hugging Face, LangChain, and Open LLM Frameworks Build Powerful NLP Systems. Fine-Tune Open LLMs. Deploy Transformers That Work in the Real World. Transformers revolutionized natural language processing - and this book shows you how to put them to work. Whether you're a machine learning engineer, data scientist, software developer, or AI startup builder, Mastering Transformers for Practical ...
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Mastering Transformers for Practical NLP A Hands-On Guide to BERT, GPT, T5, LLaMA, RAG, LoRA, and Real-World NLP Applications Using Hugging Face, LangChain, and Open LLM Frameworks Build Powerful NLP Systems. Fine-Tune Open LLMs. Deploy Transformers That Work in the Real World. Transformers revolutionized natural language processing - and this book shows you how to put them to work. Whether you're a machine learning engineer, data scientist, software developer, or AI startup builder, Mastering Transformers for Practical NLP is your complete guide to building, fine-tuning, and deploying transformer-powered applications. Inside This Book: - Train and fine-tune models like BERT, GPT, T5, LLaMA , and Falcon - Use Hugging Face Transformers, PEFT, LangChain , and ChromaDB - Implement end-to-end systems for sentiment analysis, summarization, QA, chatbots , and more - Apply Retrieval-Augmented Generation (RAG) using FAISS and custom document stores - Serve models using FastAPI, Gradio , and Streamlit - Optimize workflows with LoRA, QLoRA, quantization , and distillation - Build and deploy full-stack LLM agents , APIs, and UI prototypes What Makes This Book Different: - Developer-first design - step-by-step guides, diagrams, and working code - Production-focused - every technique is grounded in real-world deployment - Framework-agnostic thinking - learn Hugging Face, LangChain, open models, and more - Hands-on mastery - every chapter ends with challenge drills and deployment blueprints - Visual clarity - uses ASCII diagrams, flowcharts, checklists, and tables instead of images Who This Book Is For: - Engineers and developers breaking into NLP or LLM engineering - Teams building internal NLP tools or customer-facing AI products - AI researchers looking for practical implementations of transformers - Indie hackers, startup builders, and solopreneurs using open-source LLMs Includes : - 20 project-based chapters from core concepts to production APIs - Full coverage of tokenization, attention, sequence-to-sequence models, and agentic systems - Appendices with cheat sheets, CLI commands, environment setup, and ready-to-use prompt templates If you're ready to go beyond tutorials and truly master transformers for real-world NLP, this book is your blueprint. Get ready to build. Fine-tune. Deploy. Scale. Your journey into applied transformer engineering starts here.
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