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Description
GPR Exhaust System Yamaha YZ250F WR250F 2007-2011, Trioval, Full System Exhaust, Including Removable DB KillerProduction Time: 10 15 DAYS Weight: 2. 27 Lbs. 5 Kg. Length: 15. 75 in. 400 mm. GPR's Trioval series is a GPR best seller, with a classic ovoid drop shape. It is made of hand polished 304 stainless steel and has a diameter of 3. 9 inches x 5. 1 inches (100MM x 130MM). FEATURES SOUND: Upgraded sound from stock exhaust. Although louder than stock, this exhaust produces the softest sound of all the GPR exhausts. PERFORMANCE: Upgraded performance from
Production Time: 10 - 15 DAYS
Weight: 2.27 Lbs. / 5 Kg.
Length: 15.75 in. / 400 mm.
GPR's Trioval series is a GPR best-seller, with a classic ovoid drop shape. It is made of hand-polished 304 stainless steel and has a diameter of 3.9 inches x 5.1 inches (100MM x 130MM).
FEATURES
• SOUND: Upgraded sound from stock exhaust. Although louder than stock, this exhaust produces the softest sound of all the GPR exhausts.
• PERFORMANCE: Upgraded performance from stock exhaust
• QUALITY: Italian made with high-grade welding
• WEIGHT: Lighter than stock exhaust
The package includes a manifold stainless steel made, flanges, bushings, brackets. It mounts directly on the cylinders without any structural changes. Remapping the control unit may be necessary after the installation.
To install, no structural modifications are required. GPR recommends reading the included instructions or tutorial on http://www.gpr.it or the GPR channel on Youtube.
For on-line purchases, activate the warranty by sending the installation receipt from the mechanic / shop via email to [email protected], or sending the sales receipt from the physical or online store.
The exhaust has a removable db killer (noise restrictor) for racing use. Removing the DB Killer is ILLEGAL and the customer assumes the responsibility if they use the motorbike as on the circuits only, without bags, without flash lights, number plate holder or other parts that would conflict with the different angle of the gas following the transformation into the racing version. Abuse of this situation on the road will result in the loss of the product warranty and any refund request will be rejected.
The warranty is two years from the purchase, with right of reparation with a return to the GPR factory, or the nearest official distributor at the customer's expense.
GPR will not provide a new silencer, but will repair the original silencer. The customer must accept to remount the original exhaust or wait the standard time for the repair.
This is an original GPR product, developed after GPR's experience in the World Championship. It offers an innovative design, improved performance, weight savings and a full-bodied sound.
Made in Italy with a 2-year international warranty.
Tampering with the DB Killer welding or antitampering screws or fastener is illegal for road use within the EU directives. It is permitted only for RACING use in the circuits. The use of the open version (without the DB Killer) on roads does not comply with regulations governing circulation on the public road network.
This kit is homologated for noise only. Please check whether a catalyst is necessary within your country to be road-legal and to pass any local inspections.
GPR Products are plug-and-play. However, we do recommend a professional installation.
If you buy online from a seller that is NOT GPR, we recommend you buy from a seller in YOUR COUNTRY to ensure that the item arrives with the correct approvals that must also comply with local legislation. Make sure before purchasing that the seller is trustworthy and offers the items that comply your road network.
Each package includes the homologation certificate, assembly instructions, and a homologation code on each silencer.
In case of a problem during installation, please stop the installation process and immediately contact customer care via email at [email protected]
Reference: CO.Y.123.TRI
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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]
- Please click here for more details>>> Return & Exchange Policy
4.8 ★★★★★
Based on 19 reviews
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Product Reviews
★★★★★ 4
Just learning it
Format: Paperback
Nice learning book just have to finish it
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 10, 2025
★★★★★ 5
Very useful book
Format: Paperback
I use it for the machine learning class I teach.
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Reviewed in the United States on May 3, 2026
★★★★★ 5
Cover many areas in detail and recommendations for more to read for what's outside
Format: Paperback
Good book!
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Reviewed in the United States on May 4, 2026
★★★★★ 5
One of the best machine learning books...
Format: Paperback, Format: Paperback
Machine Learning can often be intimidating whether you are starting out or already a practitioner. It is easy to get stuck on one concept, walk away frustrated, or just copy that code you find on StackOverflow without really understanding what it does. What the authors of this book, Machine Learning with PyTorch and Scikit-Learn, have managed to do is to keep the reader engaged giving a deeper illustration as to how the concepts work. In this book, you get practical code examples, a detailed explanation of how the various library tools work, and exposure to the mathematical concepts behind machine learning algorithms. In addition, what I like about the book unlike many machine learning books is that the authors have managed to intuitively explain how each algorithm works, how to use them, and the mistake you need to avoid.
I have not read a Machine Learning book that better explains Transformers as this one does. The authors have managed to give a detailed dive into this model architecture through well-explained codes and illustrations. As a reader, you walk away having intuitively grasped the concepts of attention and self-attention in ways that will make this crucial NLP architecture clear. You get exposed to pre-trained models from HuggingFace library which really helps to have that hands-on experience working with large datasets.
As they have done throughout the book, the authors have broken down those complex mathematical operations into simple explanations that are easy to follow. What I generally like about the book is how it seamlessly connects all the chapters, not throwing off the reader. There are numerous external resources quoted throughout the book. This helps spark that curiosity to dig deeper. In addition, you get introduced to PyTorch, getting exposed to all those sophisticated libraries that help the reader learn how to maximize their compute power. I would say it is not intimidating at all even if you have not used PyTorch before.
I would recommend this book to anybody seeking a textbook that is both easy to read and modern in its content. If were to rate the book I will give it a 10/10 as it really applies to both beginners and experienced practitioners, covers all the concepts one needs to apply in their operations, and acts as a quick reference.
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Reviewed in the United States on March 1, 2022
★★★★★ 5
Thorough Primer for Machine Learning and PyTorch
Format: Paperback
BLUF: A thorough primer for machine learning enthusiasts with plenty of theory to underscore its many practical examples. A definite must-have for anyone looking to add PyTorch to their machine learning tool belt.
PROS:
- Extremely thorough (if not comprehensive). I really appreciate that this book doesn't just thrust one into building models with PyTorch. It starts at the "beginning" and provides examples, theory, additional resources, and citations along the way.
- Theory. Those whose calculus and linear algebra courses ended many years ago will appreciate (if not remember exactly) the mathematical theory and notation that accompanies almost every paragraph. This book gives one the opportunity to "dig deeper" or stay in the shallows until the notation stops.
- Python. Rather than simply utilizing Scikit-Learn to illustrate concepts and introduce models, this book contains many sections where models (such as a Perceptron) are coded from the ground up so the reader can fully understand the underlying mechanics. Python enthusiasts will nerd out. Parents of small children might want to skip a few pages.
- Graphs, charts, and graphics. There are plenty of places where a drier text might have foregone the use of graphs. This text does not. It does however refrain from overusing them.
- PyTorch. This should be obvious from the title, but this text prioritizes PyTorch instead of TensorFlow. This is especially helpful for those looking for an alternative to Keras and TensorFlow as the PyTorch API is very user-friendly.
CONS:
- Almost too much code. This isn't a true "con" but anyone wanting to emulate or follow along with the examples would do well to get the digital edition so they can copy and paste.
- Length and complexity. Anyone hoping for a "quick read" or a "quick start guide" will be disappointed. This book hovers somewhere between an undergraduate primer and a graduate-level text for length and readability. This is not to say that it's difficult to read, merely that there are other "quick start" / "practical" texts out there that cater more to a lay audience.
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Reviewed in the United States on February 26, 2022