SKU: 78304502597

Puig 110NA 3.0 Brems-Kuppl.Satz verfügbar für Yamaha MTT 850, D, P (Tracer, GT) (Type RN 57) 2018-

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Description

Puig 110NA 3.0 Brems-Kuppl.Satz verfügbar für Yamaha MTT 850, D, P (Tracer, GT) (Type RN 57) 2018-Part. Nr.: 110NA2609Funktion: Bremshebel Puig 3. 0 schwarz klappbar Versteller blau Puig 110NA 3. 0 Brems Kuppl. Satz pass. fuer Yamaha MTT 850, D, P (Tracer, GT) (Type RN 57) 2018 Erneuern Sie die Hebel Ihres Motorrads mit den neuen PUIG 3. 0 Hebeln. Es ist die Weiterentwicklung der Version 2. 0. PUIG hat beim entwicklen des Aussehens Wert auf die ergonomische Verbesserung des Modells gelegt um die Hebel diesbezglich zu verbessern. Nun verleihen die

Part.Nr.: 110NA2609

Funktion: Bremshebel Puig 3.0 schwarz- klappbar- Versteller blau

Puig 110NA 3.0 Brems-Kuppl.Satz pass. fuer Yamaha MTT 850, D, P (Tracer, GT) (Type RN 57) 2018-

Erneuern Sie die Hebel Ihres Motorrads mit den neuen PUIG 3.0 Hebeln. Es ist die Weiterentwicklung der Version 2.0. PUIG hat beim entwicklen des Aussehens Wert auf die ergonomische Verbesserung des Modells gelegt um die Hebel diesbezüglich zu verbessern. Nun verleihen die Hebel dem Motorrad einen moderneren und aggressiveren Touch.
Die neue Form der Hebel ermöglicht einen perfekten Griff, der mehr Grip und Zugänglichkeit garantiert und das Fahrerlebnis einzigartig macht.
Was die neuen Looks betrifft, so hat PUIG alle Grafiken, die im Stück enthalten sind, erneuert und sie an die neuesten Zeiten angepasst. Außerdem können Sie das Produkt in 7 verschiedenen Farben bekommen.

Die 3.0 PUIG-Griffe sind in 4 verschiedenen Modellen erhältlich: Klappbar, Fest, sehr Kurz und Ausziehbar und Klappbar in einem. PUIG hat seine Bemühungen darin gelegt dieses neue Modell zu verbessern. Und es ist gelungen. Die Ergonomie zu verbessern, sodass die Hände und Finger es bequem haben und gleichzeitig perfekter Halt garantiert ist.

Was die Montage betrifft, so werden die Hebel mit detaillierten Anweisungen geliefert und erfordern keine Modifikationen am Motorrad. Falls es das erste Mal ist, dass ein Griffsatz gekauft wird, müssen Sie auch den Satz spezifischer Befestigungen für Ihr Motorrad kaufen, da die Puig-Griffe nicht mit den Originalbeschlägen montiert werden. 
Die Montage der Beschläge muss von einem Fachmechaniker durchgeführt werden. Da bei der Umrüstung aufgrund vom verändern der Position der Bremspumpe das Rad mit einem Gestell angehoben werden muss. Um sicherzustellen, dass das Rad nicht gebremst ist. Wenn es abgebremst ist, kann es dazu führen, dass die Bremsen blockieren.

Puig 3.0 Griffe haben das TÜV Zertifikat und die deutsche Zulassung ABE 91294.

Kompatibel/Ersatz für Marke : Yamaha

Modell: MTT 850, D, P (Tracer, GT)

Typ: RN 57 ABE Nr: e13*00286 (VO)

Baujahr: 2018 -

Bremse: 5462N Kupplung: 8873N

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SKU: 78304502597

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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
Cuba, 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.
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Reviewed in the United States on August 10, 2025
V
Vineeth Sai
Omaha, 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!
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Reviewed in the United States on June 27, 2025
C
Verified Purchase
CL
Phoenix, US
★★★★★ 5
Loved it
Format: Paperback
I’ve easily read dozens of tech books. I liked this one a lot. Sure, there were boring parts, but most of it was engaging, especially on dry subjects. I previously read “How AI Works” and found this more informative and way more enjoyable. I got through the 700 pages in about 5 weeks while also learning about probability and linear algebra from other books and online sources. I’d love to read something more advanced by the author, maybe getting into more modern applications. I feel more comfortable with the subject and feel I am now ready to conquer more advanced texts. I initially picked this up to give me some background before reading “How to Build a LLM (from scratch)”. I’ve ordered an intermediary Deep Learning with Python book as well, but wouldn’t mind a more advanced theory book to accompany these books. I’ll definitely be rereading sections of this book to further familiarize myself with topics like backpropagation. Highly recommend if you’re looking for a gentle, but broad introduction to the topic.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 14, 2025
A
Verified Purchase
Amazon Customer
Whiting, US
★★★★★ 5
A Good Place to Start Learning AI
Format: Paperback
Diving into the world of artificial intelligence can feel like stepping into a vast, uncharted ocean, and if you're looking for a reliable vessel to navigate these waters, this book is an excellent choice. However, I must be candid—this journey is not for the faint-hearted or those hoping to breeze through. The subject of AI, with its complex algorithms and intricate theories, is notoriously challenging. You won't find yourself flipping pages at a rapid pace, as this is not a title designed for speed-reading. Instead, it demands your full attention and a willingness to engage deeply with the material. At the heart of AI lies mathematics—a fundamental pillar that underpins the entire discipline. This book, while comprehensive, offers only a glimpse into the mathematical framework that drives artificial intelligence. But don’t be disheartened by this. Think of it as a solid foundation, a primer that will arm you with the essential concepts needed before you delve deeper into the more advanced mathematical intricacies elsewhere. When you do eventually tackle those more complex equations, you'll find yourself better equipped, with a clearer understanding of the principles at play. I should also mention that I'm no stranger to Andrew's work. Having explored some of his other writings, I can confidently say that he possesses a unique flair for communication. His ability to distill complex ideas into accessible language, without losing the essence of the subject, is truly commendable. Andrew writes with a certain finesse and sophistication that makes even the most daunting topics seem approachable. His style is not just informative, but also engaging, with a touch of elegance that sets his work apart from others in the field. In summary, while the path to mastering AI is undeniably steep, this book serves as an invaluable guide. It’s not just a starting point; it’s a beacon for those who are serious about understanding the intricacies of artificial intelligence. Be prepared to invest time and effort, and in return, you'll gain a solid foothold in a subject that is as fascinating as it is complex.
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Reviewed in the United States on September 2, 2024

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