SKU: 25050626412
used peg perego high chair

used peg perego high chair Peg Perego Siesta

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Description

used peg perego high chair Peg Perego SiestaThe multifunctional, ultra compact high chair that easily accommodates a child's growth. From birth, the Siesta can be used as a recliner or as a high chair for feeding, playing and resting. The removable tray and multiple height positions allow child to sit right at the table. The Siesta follows a child from birth through the toddler years. The multi functional high chair can be used as a comfortable recliner, perfect for keeping a young baby close.

The multifunctional, ultra-compact high chair that easily accommodates a child's growth. From birth, the Siesta can be used as a recliner or as a high chair for feeding, playing and resting. The removable tray and multiple height positions allow child to sit right at the table.

The Siesta follows a child from birth through the toddler years. The multi-functional high chair can be used as a comfortable recliner, perfect for keeping a young baby close. As the child grows, the five recline positions and nine height positions provide a perfect spot for relaxing, eating or playing. Dinner will truly be a family affair, as the Siesta's multiple height settings and removable tray allow child to sit at the dinner table.

It's a smooth move from one room to the next with the Siesta. Floor-friendly caster wheels allow for an easy transition from kitchen to playroom, and automatically lock for safety. When it's time to put the Siesta away, it folds quickly and compactly. This compact fold makes the Siesta perfect for urban living spaces and is easily stored when not in use.

  • Prima Classe Upholstery- beautiful, buttery-soft upholstery is comfortable and easy to clean
  • Five reclining positions provide ultimate comfort and make it suitable for newborn, baby and toddler
  • Evolved Tilt-N-Space- seat fully reclines and extends to provide maximum comfort for child
  • Nine different height positions
  • Three-position, adjustable footrest
  • Five-point safety harness and passive restraint bar
  • Stop & Go- Mar-resistant caster wheels automatically lock for safety
  • Practical rubber storage net on seat back keeps bibs, utensils or toys within reach
  • Upholstery is stain resistant, durable, easy to remove and can be wiped clean with a damp cloth
  • Includes dishwasher-safe tray liner
  • Extremely compact, standalone fold
  • Perfect for any size living space
  • Made in Italy
Specifications
  • Folded: 11 5/6" H x 34 2/3" W
  • Unfolded: 29 1/2" H x 23 2/3" W x 41 1/6" D
  • Weight: 23.15 lb
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: 25050626412

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4.8 ★★★★★
Based on 10 reviews
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Product Reviews
O
Om S
New York, 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
Chelsea, 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
Alexandria, 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
Battle Creek, 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
Boise, 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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