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O'Reilly Media, Inc
Thársis T. P. Souza
Large Language Models The Hard Parts
N/A
2026
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Publisher > O'Reilly Media, Inc
Author > Thársis T. P. Souza
Title > Large Language Models The Hard Parts
Issue > N/A
Year > 2026
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ISBN > 9798341622524
Pages > 457
Genre > Large-Language-Models-Llms
Language > English
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Type > RETAIL
Media > Book
Format > .EPUB
Section > eBook
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Published > 2026-05
Release > 2026-05-30
Disks > 02*5.0MB
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https://bookshop.org/p/books/large-language-models-the-hard-parts-open-source-
ai-solutions-for-common-pitfalls-jr-jonathan-k-regenstein/888fd79fff718791
Large language models (LLMs) have transformed natural language processing, but
deploying them in applications introduces numerous technical challenges. Large
Language Models: The Hard Parts offers a clear, practical examination of the
limitations developers and AI engineers face when building LLM-based
applications. With a focus on implementation pitfalls (not just capabilities),
this book provides actionable strategies supported by reproducible Python code
and open source tools. Readers will learn how to navigate key obstacles in
application evaluation, input management, testing, and safety. Designed for
builders and technical product leads, this guide emphasizes practical solutions
to real-world problems and promotes a grounded understanding of LLM constraints
and trade-offs. Design testing and evaluation strategies for nondeterministic
systems Manage context, RAG, and long-context retrieval Address output
inconsistency and structural unreliability Implement safety and content
moderation frameworks Explore alignment challenges and mitigation techniques
Leverage open source models locally
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CRC32: 5c67d8b5caba246e6b6ed14b4498674f4f79ae9c