Duchess KS1243PKL Two-Handle 2-Hole Wall Mount Bridge Kitchen Faucet, Antique Brass
SKU: 37374113434

Duchess KS1243PKL Two-Handle 2-Hole Wall Mount Bridge Kitchen Faucet, Antique Brass

$137.47 $152.74
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Description

Duchess KS1243PKL Two-Handle 2-Hole Wall Mount Bridge Kitchen Faucet, Antique BrassDuchess KS1243PKL Two Handle 2 Hole Wall Mount Bridge Kitchen Faucet, Antique Brass Crafted in commendations to English nobility, the exemplary design of this faucet manifests regality and elegance with its black porcelain handles. Because of the horizontal pop that it gives, it is more of a centerpiece, perfect for planning a design around. Additionally, the unique look is great for a variety of styles from Art Deco to Farmhouse. The antique brass

Duchess KS1243PKL Two-Handle 2-Hole Wall Mount Bridge Kitchen Faucet, Antique Brass

Crafted in commendations to English nobility, the exemplary design of this faucet manifests regality and elegance with its black porcelain handles. Because of the horizontal pop that it gives, it is more of a centerpiece, perfect for planning a design around. Additionally, the unique look is great for a variety of styles from Art Deco to Farmhouse. The antique brass finish will also provide a long lasting and warm touch to your kitchen ensemble. Allow the brass construction and swivel abilities to provide a sturdy and reliant fixture as it maximizes your counter space. Glamorize your home today with the traditional elegance of this faucet.

Features

  • Solid brass construction for durability
  • Wall mount 8" center 2-hole installation
  • Drip-free ceramic disc cartridge
  • 1/2-14 NPT connection
  • 1.8 GPM/6.8 LPM spout flow rate at 60 PSI
  • 9" spout reach; 12-1/4" from wall
  • 5-3/16" spout clearance
  • 8-3/16" spout height
  • High-arc swivel spout for convenience
  • Dual lever handles meet ADA guidelines
  • Does not include side sprayer
  • High quality finishing to resist tarnishing or corrosion



Disclaimer

Kingston offers several special finishes that fall into two main groups: antiqued/distressed and living. Our antiqued/intentionally distressed finishes include Antique Brass, Antique Copper, Naples Bronze, and Black Stainless. Our living finish is Oil Rubbed Bronze. Antiqued/distressed finishes have had a darkener applied to create the appearance of patina and age. Due to the nature of plating and distressing processes, each production lot of these finishes varies slightly in brightness and tone. Some degree of inconsistency between items in antiqued or distressed finishes should be expected. We cannot guarantee an exact match between items in these finishes. The differences in tone and brightness are a variation rather than a flaw or defect. Living Finishes change over time. Our Oil Rubbed Bronze will patina over time such as taking on highlights in high-touch areas. We consider this dynamic nature a feature that gives each faucet a unique character over its lifetime of use and does not constitute a defect or flaw. Like our antiqued/distressed finishes, some degree of inconsistency between living finish items should be expected. We cannot guarantee an exact match between items in Oil Rubbed Bronze.

Downloads / Specs

Specification Sheet
Parts Diagram
Installation Guide


Compatible Parts

Compatible parts and components for this item. Please also ensure each selected additional item is compatible as appropriate.

Aerators: A556427UNSK1

Spouts: KSP1243, KSP1263, KSP1291, KSP2443

Shipping Notes
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Exchange/Return Notes
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  • Final sale items are not eligible for returns or exchanges.
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SKU: 37374113434

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4.2 ★★★★★
Based on 1564 reviews
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Product Reviews
O
Om S
Louisville, US
★★★★★ 4
Title: Really Good Book for Learning LLMs
Format: Paperback, Format: Paperback
I picked up this book after struggling with LLM implementation at work. Ken Huang explains things clearly without too much technical jargon. The book covers everything from data preparation to building AI agents. I especially liked the chapters on RAG and prompting techniques - they helped me improve my current projects. The code examples actually work, which is nice. Some parts are pretty advanced, so you need basic Python knowledge. I had to read a few chapters twice to fully get it. The fairness and bias detection section was eye-opening. Good practical advice throughout. Not just theory - real solutions you can use. Worth the money if you're serious about LLM development. Recommended for anyone building AI systems professionally.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 25, 2025
J
Jiewen Wang
Lexington, US
★★★★★ 5
a comprehensive guide at the intersection of generative AI and cybersecurity
Format: Kindle
This book blends deep theoretical foundations with practical frameworks and forward-looking strategies. From adversarial risk models to actionable guidance using OWASP Top 10 for LLMs and the NIST AI RMF, it offers both technical depth and operational clarity. What makes it stand out is its balance of academic rigor and real-world CISO insights, providing a holistic perspective on securing GenAI systems. While it leans enterprise-focused, the content remains accessible to security engineers, risk managers, and policy leaders alike. Generative AI Security is a timely and essential read for anyone working to deploy GenAI responsibly—building systems with both power and integrity in today’s fast-evolving threat landscape.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 2, 2025
N
Nader
Dallas, US
★★★★★ 1
Light on substance and heavy on flaws
Format: Paperback
The book has a great list of topics, but fails to provide much substance any of them. Most of the provided code is just comments that avoid the actual crux of the issues being discussed. (e.g. #implement the logic to validate XYZ - while the whole point of this chapter is teach how the heck we validate XYZ!) Some parts are plain wrong, for example the part on Graph based RAG is fundamentally flawed as it assumes the text embedding and the graph embedding are in the same latent space. (This is one of many more examples). Seems like the book was rushed, and the author has limited hands on experience (if any). At least we know based on the amount of flaws that it was not written by an LLM
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 31, 2025
N
noam barkay
Charlottesville, US
★★★★★ 5
Excellent book to truly understand LLM design patterns
Format: Paperback
I just finished reviewing Ken Huang's pocket book on LLM Design Patterns, and WOW what an amazing resource! This book is excellent if you want to truly understand how to create and enhance intelligent AI language models, all that in your pocket! Ken makes the difficult things seem surprisingly easy, and that's the real MAGIC. - How to prepare your data for training by making it extremely clean. Developing the brains: the practical aspects of training, optimizing, and maintaining your models. - Learn amazing prompting techniques (such as Chain-of-Thought and Tree-of-Thoughts) to improve your AI's reasoning and problem-solving abilities. Learn everything there is to know about RAGs so that your LLM can incorporate outside expertise. - It also delves into creating "agentic" AI that is capable of action and planning (not only simple plan and execute but also enhanced techniques like ReWoo!) Really, this feels like a useful toolkit, so Ken thank you for that resource Thanks, Idan Habler
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 9, 2025
R
Ryan Meyer
Los Angeles, US
★★★★★ 3
A Broad Overview, But Light on Modern Fine-Tuning
Format: Paperback
I'm currently really interested in fine-tuning LLMs and recently completed my first LoRA-based fine-tuning on a quantized model. I came to this book looking for more detail on fine-tuning. While it touches on the topic, I found the content didn’t quite align with the current state of the field in 2025. Techniques like LoRA, QLoRA, and PEFT weren’t really covered, and the material leaned more toward what I think are older or lower level approaches. That made it harder to connect with what I’m actually working on. That said, when I shifted to other chapters — like the sections on prompt engineering techniques such as Chain of Thought (CoT) and Tree of Thought (ToT) — I found more value. These sections were clearer, and I picked up a few practical insights, like using few-shot examples that walk through the CoT reasoning process. That’s not something I’ve tried before, and I can see how it might help smaller models that struggle with any type of reasoning tasks. Overall, the book feels more like a broad overview of all LLM concepts. For someone exploring many topics across the LLM ecosystem, it offers a wide-ranging introduction. But for readers like me who are actively trying to learn and apply techniques like fine-tuning and quantization, it may leave you wanting up-to-date guidance.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 10, 2025

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