Articoli correlati a Fine-Tuning Large Language Models: From Custom Datasets...
Fine-Tuning Large Language Models: From Custom Datasets to High-Performance AI Models Using Modern Toolchains - Brossura
Sinossi
Are your prompts not cutting it anymore? Fine-tuning is the next level.
This hands-on guide takes you from zero to deploying your own
custom-trained large language model using real code, modern tools,
and production-ready techniques used by AI engineers today.
Whether you want to build a medical assistant, legal document analyzer,
coding AI, or customer support bot, this book gives you the exact
pipeline to make it happen.
What you'll learn:
- How fine-tuning differs from prompt engineering and RAG and when
to use each
- LoRA and QLoRA: fine-tune powerful models on a single GPU
- How to collect, clean, and format high-quality instruction datasets
- Supervised Fine-Tuning (SFT), RLHF, and Direct Preference Optimization
- Advanced techniques: mixed precision, gradient checkpointing,
multi-GPU training
- How to evaluate, quantize, and deploy your model to production
- Safety, bias mitigation, and responsible AI practices
- 14 chapters of step-by-step projects including a chatbot,
evaluation dashboard, and automated training pipeline
This is not a theory book. Every chapter includes working Python code
using Hugging Face Transformers, PEFT, TRL, and modern open-source
models like Llama and Mistral.
By the end, you won't just understand fine-tuning you'll have built
and shipped a model of your own.
Perfect for: ML engineers, Python developers, data scientists, and
anyone ready to move beyond ChatGPT and take control of their AI stack.
Le informazioni nella sezione "Riassunto" possono far riferimento a edizioni diverse di questo titolo.
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Fine-Tuning Large Language Models: From Custom Datasets to High-Performance AI Models Using Modern Toolchains
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Paperback. Condizione: new. Paperback. Are your prompts not cutting it anymore? Fine-tuning is the next level. This hands-on guide takes you from zero to deploying your owncustom-trained large language model using real code, modern tools, and production-ready techniques used by AI engineers today. Whether you want to build a medical assistant, legal document analyzer, coding AI, or customer support bot, this book gives you the exactpipeline to make it happen. What you'll learn: - How fine-tuning differs from prompt engineering and RAG and when to use each- LoRA and QLoRA: fine-tune powerful models on a single GPU- How to collect, clean, and format high-quality instruction datasets- Supervised Fine-Tuning (SFT), RLHF, and Direct Preference Optimization- Advanced techniques: mixed precision, gradient checkpointing, multi-GPU training- How to evaluate, quantize, and deploy your model to production- Safety, bias mitigation, and responsible AI practices- 14 chapters of step-by-step projects including a chatbot, evaluation dashboard, and automated training pipeline This is not a theory book. Every chapter includes working Python codeusing Hugging Face Transformers, PEFT, TRL, and modern open-sourcemodels like Llama and Mistral. By the end, you won't just understand fine-tuning you'll have builtand shipped a model of your own. Perfect for: ML engineers, Python developers, data scientists, andanyone ready to move beyond ChatGPT and take control of their AI stack. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Codice articolo 9798182313315
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Fine-Tuning Large Language Models : From Custom Datasets to High-Performance AI Models Using Modern Toolchains
Da: AHA-BUCH GmbH, Einbeck, Germania
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Taschenbuch. Condizione: Neu. Neuware - Are your prompts not cutting it anymore Fine-tuning is the next level. This hands-on guide takes you from zero to deploying your owncustom-trained large language model using real code, modern tools, >Whether you want to build a medical assistant, legal document analyzer, coding AI, or customer support bot, this book gives you the exact>What you'll learn: - How fine-tuning differs from prompt engineering and RAG and when to use each- LoRA and QLoRA: fine-tune powerful models on a single GPU- How to collect, clean, and format high-quality instruction datasets- Supervised Fine-Tuning (SFT), RLHF, and Direct Preference Optimization- Advanced techniques: mixed precision, gradient checkpointing, multi-GPU training- How to evaluate, quantize, and deploy your model to production- Safety, bias mitigation, and responsible AI practices- 14 chapters of step-by-step projects including a chatbot, >This is not a theory book. Every chapter includes working Python codeusing Hugging Face Transformers, PEFT, TRL, and modern open-source>By the end, you won't just understand fine-tuning you'll have built>Perfect for: ML engineers, Python developers, data scientists, andanyone ready to move beyond ChatGPT and take control of their AI stack. Codice articolo 9798182313315
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