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The Cranky Man's Guide to LoRA and QLoRA
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- FormatePub
- ISBN978-1-0692859-0-4
- EAN9781069285904
- Date de parution05/08/2025
- Protection num.pas de protection
- Infos supplémentairesepub
- ÉditeurSunimage Studios Inc.
Résumé
"AGI on your toaster by Tuesday, " they promised. Hahahaha!If you're tired of the AI hype, sick of impenetrable techno-babble, and ready to get your hands dirty fine-tuning your own Large Language Models, this is the book you've been searching for. Written in a distinctly cranky, humorous, and often cynical voice by an experienced programmer who didn't just use the AI tools-he built them-this guide cuts through the jargon to deliver hard-won lessons from a thousand failures.
This is the story of one man's obsessive quest to create the ultimate AI model, sharing the successes, the near misses, and the total disasters. Most AI books are filled with abstract theory. This is not one of them. The Cranky Man's Guide to LoRA & QLoRA is built around a massive, hands-on practical section that puts you directly in the trenches. You'll follow complete, end-to-end projects that show the real, messy process of building a model-from scraping raw data to evaluating the final adapter.
Through detailed, step-by-step examples like The Sydney Experiment (training a chaotic chatbot), The Plot-Bot Project (building a creative plot writer), and a deep dive into Jane Austen Style Transfer, you'll get the battle-tested workflows you need to start training today. If you learn by doing, this is the only guide you'll need. Inside, you won't just read theory-you'll learn to: Master the Parameters: Finally understand what rank, alpha, batch size, and gradient accumulation actually do.
Tame Your Data: Uncover the tricks of data collection, cleaning, and augmentation-the real secret to a successful model. Build Your Lair: Get a no-nonsense guide to hardware and software, including building your own multi-GPU AI rig without setting your house on fire. Dodge the Errors: Learn to fix the classic CUDA meltdowns and Python tantrums that make you want to throw your computer out the window.
Choose and Quantize: Learn how to select, shrink, and prepare models for training and deployment. This book is for you if: You're a developer, tinkerer, or hobbyist tired of black-box APIs. You have a GPU and a burning desire to make it do something more interesting than render explosions. You're deeply curious about what this AI stuff is really all about, beyond the headlines. You've tried fine-tuning before and ended up with a model that speaks gibberish and an electricity bill that makes you weep.
About the Author:F. P. HAM, aka "Cranky Man, " is a senior programmer who lives and breathes this stuff. He didn't just read the manuals; he contributed to and built many of the popular training tools himself, including Training PRO, VirtualLora, Twinbook, and StoryCrafter. He's been there, done that, and has the GPU burn marks and electricity bills to prove it.
This is the story of one man's obsessive quest to create the ultimate AI model, sharing the successes, the near misses, and the total disasters. Most AI books are filled with abstract theory. This is not one of them. The Cranky Man's Guide to LoRA & QLoRA is built around a massive, hands-on practical section that puts you directly in the trenches. You'll follow complete, end-to-end projects that show the real, messy process of building a model-from scraping raw data to evaluating the final adapter.
Through detailed, step-by-step examples like The Sydney Experiment (training a chaotic chatbot), The Plot-Bot Project (building a creative plot writer), and a deep dive into Jane Austen Style Transfer, you'll get the battle-tested workflows you need to start training today. If you learn by doing, this is the only guide you'll need. Inside, you won't just read theory-you'll learn to: Master the Parameters: Finally understand what rank, alpha, batch size, and gradient accumulation actually do.
Tame Your Data: Uncover the tricks of data collection, cleaning, and augmentation-the real secret to a successful model. Build Your Lair: Get a no-nonsense guide to hardware and software, including building your own multi-GPU AI rig without setting your house on fire. Dodge the Errors: Learn to fix the classic CUDA meltdowns and Python tantrums that make you want to throw your computer out the window.
Choose and Quantize: Learn how to select, shrink, and prepare models for training and deployment. This book is for you if: You're a developer, tinkerer, or hobbyist tired of black-box APIs. You have a GPU and a burning desire to make it do something more interesting than render explosions. You're deeply curious about what this AI stuff is really all about, beyond the headlines. You've tried fine-tuning before and ended up with a model that speaks gibberish and an electricity bill that makes you weep.
About the Author:F. P. HAM, aka "Cranky Man, " is a senior programmer who lives and breathes this stuff. He didn't just read the manuals; he contributed to and built many of the popular training tools himself, including Training PRO, VirtualLora, Twinbook, and StoryCrafter. He's been there, done that, and has the GPU burn marks and electricity bills to prove it.
"AGI on your toaster by Tuesday, " they promised. Hahahaha!If you're tired of the AI hype, sick of impenetrable techno-babble, and ready to get your hands dirty fine-tuning your own Large Language Models, this is the book you've been searching for. Written in a distinctly cranky, humorous, and often cynical voice by an experienced programmer who didn't just use the AI tools-he built them-this guide cuts through the jargon to deliver hard-won lessons from a thousand failures.
This is the story of one man's obsessive quest to create the ultimate AI model, sharing the successes, the near misses, and the total disasters. Most AI books are filled with abstract theory. This is not one of them. The Cranky Man's Guide to LoRA & QLoRA is built around a massive, hands-on practical section that puts you directly in the trenches. You'll follow complete, end-to-end projects that show the real, messy process of building a model-from scraping raw data to evaluating the final adapter.
Through detailed, step-by-step examples like The Sydney Experiment (training a chaotic chatbot), The Plot-Bot Project (building a creative plot writer), and a deep dive into Jane Austen Style Transfer, you'll get the battle-tested workflows you need to start training today. If you learn by doing, this is the only guide you'll need. Inside, you won't just read theory-you'll learn to: Master the Parameters: Finally understand what rank, alpha, batch size, and gradient accumulation actually do.
Tame Your Data: Uncover the tricks of data collection, cleaning, and augmentation-the real secret to a successful model. Build Your Lair: Get a no-nonsense guide to hardware and software, including building your own multi-GPU AI rig without setting your house on fire. Dodge the Errors: Learn to fix the classic CUDA meltdowns and Python tantrums that make you want to throw your computer out the window.
Choose and Quantize: Learn how to select, shrink, and prepare models for training and deployment. This book is for you if: You're a developer, tinkerer, or hobbyist tired of black-box APIs. You have a GPU and a burning desire to make it do something more interesting than render explosions. You're deeply curious about what this AI stuff is really all about, beyond the headlines. You've tried fine-tuning before and ended up with a model that speaks gibberish and an electricity bill that makes you weep.
About the Author:F. P. HAM, aka "Cranky Man, " is a senior programmer who lives and breathes this stuff. He didn't just read the manuals; he contributed to and built many of the popular training tools himself, including Training PRO, VirtualLora, Twinbook, and StoryCrafter. He's been there, done that, and has the GPU burn marks and electricity bills to prove it.
This is the story of one man's obsessive quest to create the ultimate AI model, sharing the successes, the near misses, and the total disasters. Most AI books are filled with abstract theory. This is not one of them. The Cranky Man's Guide to LoRA & QLoRA is built around a massive, hands-on practical section that puts you directly in the trenches. You'll follow complete, end-to-end projects that show the real, messy process of building a model-from scraping raw data to evaluating the final adapter.
Through detailed, step-by-step examples like The Sydney Experiment (training a chaotic chatbot), The Plot-Bot Project (building a creative plot writer), and a deep dive into Jane Austen Style Transfer, you'll get the battle-tested workflows you need to start training today. If you learn by doing, this is the only guide you'll need. Inside, you won't just read theory-you'll learn to: Master the Parameters: Finally understand what rank, alpha, batch size, and gradient accumulation actually do.
Tame Your Data: Uncover the tricks of data collection, cleaning, and augmentation-the real secret to a successful model. Build Your Lair: Get a no-nonsense guide to hardware and software, including building your own multi-GPU AI rig without setting your house on fire. Dodge the Errors: Learn to fix the classic CUDA meltdowns and Python tantrums that make you want to throw your computer out the window.
Choose and Quantize: Learn how to select, shrink, and prepare models for training and deployment. This book is for you if: You're a developer, tinkerer, or hobbyist tired of black-box APIs. You have a GPU and a burning desire to make it do something more interesting than render explosions. You're deeply curious about what this AI stuff is really all about, beyond the headlines. You've tried fine-tuning before and ended up with a model that speaks gibberish and an electricity bill that makes you weep.
About the Author:F. P. HAM, aka "Cranky Man, " is a senior programmer who lives and breathes this stuff. He didn't just read the manuals; he contributed to and built many of the popular training tools himself, including Training PRO, VirtualLora, Twinbook, and StoryCrafter. He's been there, done that, and has the GPU burn marks and electricity bills to prove it.