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Description
tiger mist brown dress MYLES DRESSDetails Chocolate brown maxi dress Fitted silhouette Halter style with true tie straps at centre back Featuring gold coloured o ring details at shoulder straps Deep v neckline Thigh high side seam split Asymmetrical panels Slight cowl at back neckline Pull on construction Slip into with ease Size and Fit True to size. We recommend wearing your standard size Fitted Designed to perfectly skim the body Maxi length Style sits approximately at ankle point
Details
- Chocolate brown maxi dress
- Fitted silhouette
- Halter style with true-tie straps at centre back
- Featuring gold coloured o-ring details at shoulder straps
- Deep v-neckline
- Thigh-high side seam split
- Asymmetrical panels
- Slight cowl at back neckline
- Pull-on construction - Slip into with ease
Size and Fit
Fabric
- 96% Polyester 4% Elastane
- Stretch = High stretch. This fabric is extremely stretchy for a snug fit
- Our favourite buttery jersey - Super stretchy for the comfiest bodycon fit
- Fully lined
- Colour may vary due to lighting on images. The product images (without model) are closest to the product's true colour.
Care Instructions
It's recommended to follow the below care instructions:
- Wash and dry garment inside out
- Cold hand wash
- Dry flat in shade
- Cool iron on reverse
- Do not iron embellishment
- Do not bleach
- Do not tumble dry
-
Do not dry clean
Model Information
- Emily (Model 1): Size XS, Height: 170/5’7”, Bust: 81/32, Hips 82/32, Waist: 59/23
- Yasmin (Model 2): Size S, Height: 174/5'8, Bust: 82/32, Waist: 63/24, Hips: 92/36
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- 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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4.1 ★★★★★
Based on 1508 reviews
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Product Reviews
★★★★★ 4
Understanding AI prompts as a science
Format: Audiobook
Prompt engineering is the art and science of finding the right words to generate the right responses from artificial intelligence (AI). It's becoming a skill in-demand in today's workplaces. It's also becoming an essential skill for life. To understand prompt engineering, you must understand how AI tools understand their inputs. This book explains that to you in many forms.
It covers prompting as it intersects all the major AI disciplines, like general prompts (as in a ChatBot), fine-tuning, and retrieval-augmented generation (RAG). It also introduces how prompting intersects a couple of image-generation tools.
As a scientist, I appreciate the theoretical approach to these practical matters. Too many people are hacks at AI these days, and any technical understanding can rapidly advance an individual's effectiveness. Prompt engineering is often made fun of as a "soft" topic, but as this book demonstrates, it intersects all the major AI areas. Presumably less garbage in means less garbage out. This book shows how you can make that take place.
As typical for O'Reilly materials, this book appeals to people who desire an intermediate-to-advanced understanding of how AI works. It's not for the casual user. Anyone technical involved in professional knowledge generation using AI can benefit from understanding the dynamics "under the hood." It's a good, though perhaps not ground-breaking, textbook for those of us unable to take a class in the subject. Prompt engineering may be a soft topic to many, but books like this ground the field in the science that can make or break a digital or software product.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 13, 2025
★★★★★ 5
Great book
Format: Paperback
Great book! It is helpful as I work towards my Masters of Science in Applied Artificial Intelligence
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on December 20, 2025
★★★★★ 5
Comprehensive Guide with Practical Insights
Format: Paperback
This is a solid book for understanding the art and science of working with LLMs and other generative AI models. I always struggled with getting the output I was looking for, and wasn't sure how best to "ask" the models for what I wanted. This book did a great job of laying out the strategies and practical guidance to craft the prompts. There were a lot of tips and tricks, but the overall understanding and framework around prompt engineering has been super useful.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 25, 2024
★★★★★ 5
A must read!
Format: Paperback
Hands down, the best book on prompt engineering and implementing LLMs. Really enjoyed Michael and James deep dive. Whether you're technical or not, this book is foundational to a deeper understanding in how to properly explore and implement LLMs.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on June 25, 2024
★★★★★ 4
Helpful for GPT/LangChain framework
Format: Paperback
I applaud the authors for putting forth a comprehensive introduction in a rapidly evolving space. I absorbed a lot, helpful as I was developing a prototype — using open source methods.
And that’s where I was disappointed. The LLM and examples are highly adapted to OpenAI’s GPT-x and the bulky LangChain framework, something not obvious until you dig in to the book. Sure, this may be where newbie demand was when the authors began writing. But as the open source models and OpenAI alternatives gain speed (e.g. Llama 3.1, Groq, etc.) this book may quickly need an updated and expanded version to stay relevant.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on August 7, 2024
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