SKU: 54982265832

NUX Horseman Dual Overdrive

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Description

NUX Horseman Dual OverdriveThey say: Two in One Overdrive Pedal One of the most sought after dual overdrive pedals produced in the mid '90s is now in one unique pedal design with a pocket size. NuX Horseman pays homage to the legendary Centaur pedal. There are 3 dials for primary settings and 2 modes: Gold and Silver, and it offers massive headway usually requiring an 18v input. Gold Mode mimics its classic predecessor; the transparent Gold Centaur overdrive pedal and the

They say:

Two-in-One Overdrive Pedal

One of the most sought-after dual overdrive pedals produced in the mid '90s is now in one unique pedal design-with a pocket size. NuX Horseman pays homage to the legendary Centaur pedal. There are 3 dials for primary settings and 2 modes: Gold and Silver, and it offers massive headway usually requiring an 18v input.

Gold Mode mimics its classic predecessor; the transparent Gold Centaur overdrive pedal and the Silver Mode is a powered-up version with an extended gain range (Silver Centaur).

NuX Unique Design
The sound is based on the Centaur's voltage converter circuit. But the Horseman's characteristic design is crafted with a built-in OP-AMP voltage-converter driving the 18V to OP-AMP. Higher voltage-supply orders-up more harmonics, and convincingly reproduces the sound of this unique pedal.

Clean Boost
Another “classic” way to use the NuX Horseman.   Very useful when used in combination with the amplifiers drive channel (or any other drive pedal).  And, depending on the Gain - Output adjustment, it lets the Horseman be used as a clean boost.  Dial-up a low-gain with a high output setting, and it adds mostly volume and minimal color to your sound. 

Natural Distortion

Additionally, the controls can be set to distort the sound signal in the pedal, where two Schottky diodes can perform a waveform clipping. (The germanium diodes are discontinued, we especially select the Schottky diodes to replicate the waveform clipping ) The "gain" knob is a double potentiometer (a "dual-ganged gain pot"), which controls bass and middle frequencies. Treble and volume are each controlled with separate knobs.

True/Buffer Bypass
NuX Horseman has an optional bypass mode. You can use the pedal in True Bypass mode to keep your signal untouched when the pedal is OFF in the chain. We highly recommend to select buffer bypass mode if you have more than 4 pedals connected together; switch to Buffer Bypass mode and there will be no signal loss in your pedal chain! 

Push and hold the footswitch and power-up the pedal; the LED indicator will show which bypass mode is activated; RED - True Bypass / GREEN - Buffer Bypass.

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SKU: 54982265832

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4.5 ★★★★★
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Product Reviews
J
Jiewen Wang
Carnegie, 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
Draper, 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
Port Orchard, 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
Massapequa, 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
V
Vineeth Sai
Massapequa, US
★★★★★ 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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