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Description
Native Trails 36" Freestanding Vanity Base in Chardonnay, Reclaimed Oak Wood, Vintner's Collection, VNW361Native Trails 36" Freestanding Vanity Base in Chardonnay, Reclaimed Oak Wood, Vintner's Collection, VNW361 The Chardonnay Vanity transforms an authentic piece of California's wine country into a beautifully functional wood vanity base. Handcrafted from reclaimed oak staves used to flavor wine during the fermenting process, each vanity has one of a kind coloration protected by a low VOC finish. Pair with Native Trails Chardonnay Mirror. Available In:
Native Trails 36" Freestanding Vanity Base in Chardonnay, Reclaimed Oak Wood, Vintner's Collection, VNW361
The Chardonnay Vanity transforms an authentic piece of California's wine country into a beautifully functional wood vanity base. Handcrafted from reclaimed oak staves used to flavor wine during the fermenting process, each vanity has one-of-a-kind coloration protected by a low-VOC finish. Pair with Native Trails Chardonnay Mirror.
Available In:
Features
- Handcrafted in the USA
- Constructed from reclaimed oaking staves for exceptional strength and a rustic appearance
- Vintner's Collection vanity bases are hand-crafted by artisans using repurposed oak barrels and oak staves from wineries along the California Central Coast
- Vanity features four full-extension soft-close drawers providing ample concealed storage space
- Removable front panel for easy plumbing access and hidden storage
- Features a custom-blended wax applied by hand
- Solid construction and assembly provide years of reliable performance
- Pair with surface mounted sink less than 7 inches deep
- Covered under Native Trails limited lifetime warranty
- Due to their handcrafted nature, no two products will be exactly the same and may vary in finish, texture and other details
- 36-inch Vanity Base will fit an NSV36 Vanity Tops
This item is a Vanity Base and needs a coordinating Native Trails Sink and Vanity Top to be used as a Bathroom Vanity. Please contact us for help with configuring the full vanity set.
Details
| Box Height: | 24" |
|---|---|
| Box Length: | 34" |
| Box Weight: | 125 lb(s) |
| Box Width: | 37" |
| Cabinet Material: | Reclaimed Wood |
| Collection: | Vintner's |
| Color: | Chardonnay |
| Country of Origin: | USA |
| Finish: | Chardonnay |
| Freight Class (LTL Only): | 250 |
| Harmonized System Code: | 9403.60.0000 |
| Installation Type: | Freestanding |
| Item Height: | 34" |
| Item Length (Front to Back): | 21.5" |
| Item Weight: | 120 lb(s) |
| Item Width (Side to Side): | 36" |
| Material: | Reclaimed Wood |
| NMFC Code: | 79300-04 |
| Overall Dimensions: | 36" x 21.5" x 34" |
| Palletized Dimensions (LTL Only): | 40" x 48" x 40" |
| Palletized Weight (LTL Only): | 165 |
| Shape: | Rectangle |
| Sku: | VNW361 |
| Ship Method: | LTL |
Warranty
Native Trails Warranty Details (PDF)
Installation Instructions
Product Care
Native Trails Product Care (PDF)
Video(s)
Shipping Notes
- Free Standard Shipping on $100+ Orders to the USA.
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Exchange/Return Notes
- We offer a 30-day return/exchange service after receiving.
- Final sale items are not eligible for returns or exchanges.
- To process your return/exchange, please contact us at [email protected]
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4.3 ★★★★★
Based on 12 reviews
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Product Reviews
★★★★★ 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
★★★★★ 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
★★★★★ 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
★★★★★ 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.
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Reviewed in the United States on August 10, 2025
★★★★★ 5
Great foundation read for security!
Format: Paperback
This book is a great read! It builds a strong foundation and I would highly recommend it for builders who are interetsed in building on LLMs and ensuring everything is secure. Security is super important and this book does it justice!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 27, 2025
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