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LLM Fine Tuning with Open Models: Efficient Training, Adaptation, and Deployment with LoRA, QLoRA, and PEFT
Paperback
Publisher: Independently Published
Published: Jul 18 2025
Pages: 162
Weight: 0.50
Height: 0.35 Width: 6.00 Depth: 9.00
Language: English
LLM Fine-Tuning with Open Models: Efficient Training, Adaptation, and Deployment with LoRA, QLoRA, and PEFT
Unlock the full potential of Large Language Models (LLMs) for your business, product, or research. This hands-on guide shows you how to fine-tune, align, and deploy powerful models like LLaMA, Mistral, Falcon, and more-without needing massive compute.Inside you'll learn how to:
- Prepare and fine-tune models on custom datasets
- Use parameter-efficient methods to cut costs and training time
- Evaluate, align, and optimize LLM outputs for safety and accuracy
- Build real-time apps, APIs, and agents powered by your fine-tuned model
- Deploy production-ready AI with ONNX, FSDP, and quantized models
Perfect for developers, ML engineers, startup teams, and tech leads looking to take control of Generative AI. No hype-just actionable techniques for training and deploying smarter, leaner, and safer AI systems.
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