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Performance, hallucinations, accuracy, and bias
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Look inside
Tested strategies to reduce hallucinations, improve performance and cost efficiency, and reduce bias or unethical behavior in your LLMs outputs.
LLM Reliability shows you exactly how to guide large language models from research prototypes to scalable, robust, and efficient production systems. From model training to maintenance, an engineer will find everything they need to work with LLMs in this one-stop guide.
Inside LLM Reliability you’ll learn how to:
LLM Reliability is a guide to putting LLMs into production in the real world. The book bridges the gap between theory and practice. You’ll go beyond basics like prompting into advanced optimizations: intelligent agents, Retrieval Augmented Generation (RAG), and in-depth solutions for mitigating hallucinations and bias.
LLM Reliability shows you exactly how to guide large language models from research prototypes to scalable, robust, and efficient production systems. From model training to maintenance, an engineer will find everything they need to work with LLMs in this one-stop guide.
Inside LLM Reliability you’ll learn how to:
- Deploy LLMs into production
- Detect and reduce hallucinations
- Mitigate bias
- Optimize LLM performance and resource usage
- Advanced prompt engineering techniques
- Build intelligent agents and Retrieval-Augmented Generation
LLM Reliability is a guide to putting LLMs into production in the real world. The book bridges the gap between theory and practice. You’ll go beyond basics like prompting into advanced optimizations: intelligent agents, Retrieval Augmented Generation (RAG), and in-depth solutions for mitigating hallucinations and bias.
LLM Reliability ebook for free
