SKU: 98955647733

Biscuits sablés aux pépites de chocolat - boite métal "Louison à Paris" 150g

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Description

Biscuits sablés aux pépites de chocolat - boite métal "Louison à Paris" 150gLe produit Lauthentique Petit Sabl aux ppites de chocolat dans notre nouveau dcor Parisien ! Poids net 150g La recette Petit Sabl Ppites de Chocolat La Sablsienne fabrique le vritable Sabl de Sabl Sur Sarthe, rond, dentel, croquant et pur beurre frais. La recette sest transmise de gnration en gnration dans la ville dont elle porte le nom. Elle est aujourdhui reconnue comme une spcialit du patrimoine culinaire franais. La Marquise de Sabl, a t en 1670

Le produit

L’authentique Petit Sablé aux pépites de chocolat dans notre nouveau décor Parisien !

Poids net 150g

La recette

Petit Sablé Pépites de Chocolat

La Sablésienne fabrique le véritable Sablé de Sablé-Sur-Sarthe, rond, dentelé, croquant et pur beurre frais. La recette s’est transmise de génération en génération dans la ville dont elle porte le nom. Elle est aujourd’hui reconnue comme une spécialité du patrimoine culinaire français.

La Marquise de Sablé, a été en 1670 la première ambassadrice de ces petits sablés à la cour du Grand Condé. Le Petit Sablé est fabriqué par notre biscuiterie, à partir d’ingrédients naturels dont les matières premières proviennent principalement de l’Ouest de la France : pur beurre frais des Pays de la Loire, farine de meuniers Sarthois, œufs de poules élevées en plein air.

Le Petit Sablé est décliné en différentes recettes :
- Aux pépites de chocolat : fabriqués avec du pur beurre de cacao
- Aux pépites de caramel au sel de Guérande
- Aux pépites de fruits (abricot, framboise, citron) : approvisionnés localement par un producteur du sud de la France
- Aux pépites de pomme et de caramel : élaborés avec des pommes françaises et un caramel doré, pour un goût à la fois fruité et généreux qui rappelle les desserts d’antan.
- Tout chocolat : fabriqué avec de la poudre de cacao pour un goût intense en chocolat
- Fève tonka : graine d’Amérique du sud, de forme allongée et de couloir noire. Présente des arômes d’amande, de caramel et de vanille voire de café.
- Thé bergamote : subtilement parfumé à l’essence naturelle de bergamote, inspiré du célèbre thé Earl Grey, pour une note délicate et raffinée.
La recette que nous vous proposons ici est celle des sablés La Sablésienne. La Sablésienne propose un autre type de recette de sablés : les sablés 1670 Marquise de Sablé.

Ces deux recettes se distinguent par la quantité de beurre et d’œufs, plus élevée dans la recette 1670. De plus, elle ne contient pas de poudre à lever, ce qui donne aux sablés une forme moins bombée que les sablés La Sablésienne. Dans la recette La Sablésienne, l’œuf est appliqué sur le sablé pour le faire dorer, tandis que dans la recette 1670, l’œuf est intégré à la pâte, conférant ainsi au sablé une texture légèrement plus fondante alors que l’autre recette est plus croquante.

Ingrédients : Farine de blé, Beurre frais, Sucre, Pépites de chocolat, Œufs, Sel, Lait écrémé en poudre, Poudre à lever : bicarbonate de sodium

Valeurs Nutritives (100g) : Energie 2065kJ / 493kcal, matières grasses 21.7g dont acides gras saturés 15g, glucides 66.3g dont sucres 32.1g, protéines 6.8g, sel 0.7g

Allergènes : Fabriqué dans un atelier qui utilise du SESAME, du SOJA et des FRUITS à COQUE.

La Marque

La Sablésienne

La Sablésienne est notre marque emblématique. Fondée en 1962 à Sablé-sur-Sarthe, la ville qui a donné son nom au célèbre biscuit sablé, la Sablésienne est fière de ses méthodes de production qui respectent les recettes traditionnelles, garantissant une qualité et une saveur authentiques dans chaque biscuit. Nous conservons notre héritage tout en intégrant des innovations pour répondre aux goûts contemporains. Les produits de La Sablésienne promettent une expérience gustative inoubliable, ancrée dans l’authenticité et le raffinement.

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SKU: 98955647733

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4.3 ★★★★★
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N
Nader
Whiting, 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
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
Charlottesville, 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
West Palm Beach, 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
C
Verified Purchase
CL
Massapequa, 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

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