


AVS 08-12 Chevy Malibu Ventvisor Outside Mount Window Deflectors 4pc - Smoke
Marsoni
M251S
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Friday, May 29
AVS 08-12 Chevy Malibu Ventvisor Outside Mount Window Deflectors 4pc - SmokeSKU: 94068 UPC: 725478101980 AVS 08 12 Chevy Malibu Ventvisor Outside Mount Window Deflectors 4pc Smoke AVS Original Ventvisor side window deflectors deliver precise fit for 2008 2012 Chevrolet Malibu models, including LS, LT, LTZ, Hybrid, Classic LS and Classic LT. These smoke tinted 4 piece sets mount outside the window frame using pre applied 3M automotive adhesive for no drill installation. Drive with windows down to enjoy fresh air circulation
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★★★★★ 5
Lim provides an easy-to-follow path to get an LLM-powered app up and running
Format: Kindle
Lim has written another really clear, easy-to-follow tutorial. This one walked me through the Ollama platform showing step-by-step how to download open weight models, query them, supply them with my own documents, and write applications that are powered by LLMs. Lim provides an easy-to-follow path to get the first version of an LLM-powered app up and running.
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Reviewed in the United States on February 20, 2026
★★★★★ 5
Excellent roadmap for the local AI jungle
Format: Paperback
Great little book.
Every page has something useful. No fluff. Clearly written by someone whose been in the trenches lol
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Reviewed in the United States on September 23, 2025
★★★★★ 5
Great primer for building LLM Applications
Format: Kindle
I highly recommend the book for anyone who wants to come up to speed on running Ollama for open models. The book is well structure and teach you how to create a working RAG Application. I recommend as a primer for anyone interested in building LLM Applications.
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Reviewed in the United States on May 5, 2025
★★★★★ 5
Breaks down complex concepts into bite-sized, practical chapters.
Format: Kindle
This hands-on guide to Ollama is exactly what I needed! The author breaks down complex concepts into bite-sized, practical chapters that get straight to the point. The sections on different Ollama models and customization were particularly helpful. If you're looking to learn about building local LLM-powered applications without any fluff, this book is a great investment.
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Reviewed in the United States on February 21, 2025
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Great helpful book.
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