SKU: 39869555103

大瑪 螺螄粉全素系列 DaMa Luosifen

Sale price$19.80 Regular price$22.00
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Description

大瑪 螺螄粉全素系列 DaMa Luosifen() (279gx1) () (234gx1) () (234gx6) [(27%)][()] L ()((L 5' 5' )()[][][L ()][L () () () ] [L ] 279(1)234(1) 12 () (234g)(1)

→(全素)大瑪螺螄粉-袋裝(279gx1袋)

🔥正宗柳州大瑪螺螄粉🔥
.火鍋湯底最能呈現鮮、燙、酸、爽、辣的螺螄特有風味。
.相關原料均尊重柳州原味,通過食藥署檢驗,經海關合法進口。
.無任何動物成份、無五辛,螺螄湯頭濃郁,源自馬來西亞獨特香料
.內附濃縮螺螄湯料包、腐竹花生包、老罈酸筍包、花椒辣油包、醇香醋包,
.所有調料均獨立包裝,口味及份量隨喜好自行調整添加。

 

→(全素)大瑪螺螄粉-碗裝(234gx1碗)

🔥正宗柳州大瑪螺螄粉🔥
.火鍋湯底最能呈現鮮、燙、酸、爽、辣的螺螄特有風味。
.相關原料均尊重柳州原味,通過食藥署檢驗,經海關合法進口。
.無任何動物成份、無五辛,螺螄湯頭濃郁,源自馬來西亞獨特香料
.內附濃縮螺螄湯料包、腐竹花生包、老罈酸筍包、花椒辣油包、醇香醋包,
.所有調料均獨立包裝,口味及份量隨喜好自行調整添加。

 

→(全素)大瑪螺螄粉-碗裝(234gx6碗)

🔥正宗柳州大瑪螺螄粉🔥
.火鍋湯底最能呈現鮮、燙、酸、爽、辣的螺螄特有風味。
.相關原料均尊重柳州原味,通過食藥署檢驗,經海關合法進口。
.無任何動物成份、無五辛,螺螄湯頭濃郁,源自馬來西亞獨特香料
.內附濃縮螺螄湯料包、腐竹花生包、老罈酸筍包、花椒辣油包、醇香醋包,
.所有調料均獨立包裝,口味及份量隨喜好自行調整添加。

【商品資訊】

.成分:麵體[米(27%)、玉米澱粉、水]、湯包[水、大豆油、棕櫚油、豆瓣醬(辣椒、蠶豆、鹽、小麥粉、防腐劑(己二烯酸鉀))]、黃豆醬(水、大豆、小麥粉、鹽)、糖、酵母提取物、醬油(水、鹽、   黃豆、小麥、小麥粉、普通焦糖色素、L-麩酸鈉、糖、防腐劑(己二烯酸鉀)、草菇)、竹筍、辣椒、香菇調味料((L-麩酸鈉、 麥芽糊精、鹽、香菇粉、5'-次黃嘌呤核苷磷酸二鈉、5'-鳥嘌呤核苷磷酸二鈉)、白胡椒粉、花椒、丁香、防腐劑(己二烯酸鉀)、調味包[大豆油、辣椒、花椒、茴香、丁香、紅椒色素、辣椒提取物、辣椒香料]、醋包[水、大米、鹽]、酸筍[竹筍、水、鹽、L-麩酸鈉、冰糖、辣椒粉、防腐劑(己二烯酸鉀)]、蔬菜包[醃酸豆角(長豆、水、鹽)、醃蘿蔔(蘿蔔乾、鹽、L-麩酸鈉、檸檬酸、防腐劑(己二烯酸鉀) 、防腐劑(苯甲酸鈉))、木耳、辣椒粉、 冰糖、防腐劑(己二烯酸鉀) ]、 配料包[花生、腐竹(黃豆、水、小麥粉、鹽)、棕櫚油、鹽、糖、L-麩酸鈉]

.淨重:279公克(1袋)、234克(1碗)

.保存期限:12個月

.產地:馬來西亞

※本產品實物包含有小麥、大豆、蠶豆、花生及其製品,不適合對其過敏體質者食用。

 

→(全素)大瑪螺螄粉-碗裝(234g)(1入)

🔥正宗柳州大瑪螺螄粉🔥
.火鍋湯底最能呈現鮮、燙、酸、爽、辣的螺螄特有風味。
.相關原料均尊重柳州原味,通過食藥署檢驗,經海關合法進口。
.無任何動物成份、無五辛,螺螄湯頭濃郁,源自馬來西亞獨特香料
.內附濃縮螺螄湯料包、腐竹花生包、老罈酸筍包、花椒辣油包、醇香醋包,
.所有調料均獨立包裝,口味及份量隨喜好自行調整添加。

 

 

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Reviewed in the United States on March 1, 2024
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Massapequa, US
★★★★★ 5
The Basement is a Safe Place
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The Basement by Tim Ross is a book full of Bible, insight, and words of wisdom that only Tim Ross and the Holy Spirit can provide. Each page has tips for everyday living and how you too can upset the world with the message of love and hope of Jesus Christ. Read the book and join the Dwellers in the basement for a whole new perspective on life with Jesus.
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Reviewed in the United States on February 27, 2024
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Paul Pollock
San Leandro, US
★★★★★ 5
Your Blueprint for Building Smarter AI!
Format: Paperback
If you're building AI and sometimes feel a bit lost, "LLM Design Patterns" by Ken Huang is like finding the secret map you've been searching for. Ken Huang, who clearly knows his stuff (he's a renowned AI expert and works with big names like OWASP and NIST), writes in a way that just clicks, without getting bogged down in super-dense tech talk. The author even acknowledges using AI to make the language clearer for a smooth reading experience! This book covers everything you need, from getting your data squeaky clean to making AI agents that can actually think and act autonomously. For me, the parts on Retrieval-Augmented Generation (RAG) and advanced ways to 'talk' to your AI (prompting) were particularly eye-opening and immediately useful for my projects. Plus, it has handy code snippets that really help you grasp the ideas. While they're not ready for direct production copy-pasting, they illustrate the concepts perfectly for learning. It's not for absolute beginners – you'll want some basic Python and machine learning smarts to get the most out of it – but the effort is totally worth it. It even delves into making sure your AI is fair and unbiased, which was a real lightbulb moment for me. This book is crammed with actionable advice; it's less about abstract theory and more about real-world solutions you can actually use. If you're serious about building impressive AI systems professionally, this is a must-read.
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Reviewed in the United States on August 7, 2025
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Allen Wyma
Lake Worth, US
★★★★★ 5
Great Resource when Integrating AI
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Om S
Omaha, US
★★★★★ 4
Title: Really Good Book for Learning LLMs
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I picked up this book after struggling with LLM implementation at work. Ken Huang explains things clearly without too much technical jargon. The book covers everything from data preparation to building AI agents. I especially liked the chapters on RAG and prompting techniques - they helped me improve my current projects. The code examples actually work, which is nice. Some parts are pretty advanced, so you need basic Python knowledge. I had to read a few chapters twice to fully get it. The fairness and bias detection section was eye-opening. Good practical advice throughout. Not just theory - real solutions you can use. Worth the money if you're serious about LLM development. Recommended for anyone building AI systems professionally.
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