PyTorch LLM: Train, Fine-Tune, and Deploy Large Language Models for Real-World Applications

Sprinter, Charles

ISBN 13: 9798300768577

Editore: Independently published, 2024

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Dati bibliografici

• Titolo: PyTorch LLM: Train, Fine-Tune, and Deploy Large Language Models for Real-World Applications
• Editore: Independently published
• Data di pubblicazione: 2024
• Lingua: Inglese
• ISBN 13: 9798300768577
• Rilegatura: Brossura
• Condizione: New

Descrizione articolo

Riassunto

PyTorch LLM: Train, Fine-Tune, and Deploy Large Language Models for Real-World Applications

PyTorch has emerged as one of the most powerful and flexible deep learning frameworks, enabling developers, data scientists, and researchers to build cutting-edge AI systems. In today’s AI-driven world, Large Language Models (LLMs) such as BERT, GPT, T5, and LLaMA are revolutionizing natural language processing and transforming industries like healthcare, finance, education, and customer service.

This comprehensive, hands-on guide takes you step-by-step through the entire lifecycle of working with LLMs using PyTorch—from foundations and model building to fine-tuning and deployment. Whether you are just getting started or already experienced with deep learning, this book provides practical knowledge and real-world examples to help you create scalable, production-ready language models.

What You’ll Learn:

• Core Foundations: Understand the principles behind LLMs and transformer-based architectures.

• Training and Fine-Tuning: Build models from scratch or fine-tune pre-trained models for specialized tasks like chatbots, summarization, and text classification.

• Hands-On Code: Over 50 detailed, fully-tested code examples that you can run and adapt for your own projects.

• Real-World Applications: Explore case studies in industries such as finance, healthcare, retail, and education.

• Advanced Techniques: Dive into distributed computing, multi-GPU training, and optimizations for large-scale models.

• Deployment Strategies: Learn how to deploy models with PyTorch on cloud platforms such as AWS, Google Cloud, and Azure.

• Model Interpretability: Gain insights into model decisions using tools like Captum to ensure fairness and transparency.

Who This Book Is For:

• Data Scientists and ML Engineers looking to master modern NLP and LLM development.

• Software Engineers aiming to integrate advanced AI features into applications.

• AI Researchers exploring cutting-edge PyTorch capabilities and experimentation.

• AI Enthusiasts and Learners eager to gain practical, job-ready skills in deep learning and NLP.

By the end of this book, you’ll be equipped to build, fine-tune, and deploy powerful LLMs that solve real-world problems and deliver value across multiple industries. With clear explanations, practical projects, and production-focused strategies, this book will be your go-to resource for mastering PyTorch and modern language modeling.