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در این مقاله و مقاله جدیدی که در اومده
RAG
🔹
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
🔹

✔️مدل های RAG، ساختار جدیدی برای مدل های Retrieval هستن که با knowledge سرو کار دارن و تلاش میکنند وقتی جنریت میکنن نالج محور باشن!
✔️ منظور از knowledge، هر دیتابیسی که شامل اطلاعاتی هستش مثل ویکی پدیا، البته فقط ویکی پدیا نیست لزوما
✔️ همونطور که گفتم این یک ساختار جدید هستش، Seq2Seq و نسبت به ساختار های E2E عادی و همچنین کاندیدا محور بهتر کار کرده.
✔️به خاطر محبوبیت و کاراییش، Huggingface هم این ساختار رو به کتابخونه ترنسفورمر ها اضافه کرده.
▪️

Introducing Self-RAG, a new easy-to-train, customizable, and powerful framework for making an LM learn to retrieve, generate, and critique its own outputs and retrieved passages, by using model-predicted reflection tokens.

📜 Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
🌐 Project

#مقاله #ایده_جذاب #دیتاست

🔸 مطالب بیشتر 👇👇

✅ @AI_DeepMind
🔸 @AI_Person
▪️ @css_nlp

arXiv
Forwarded from AI DeepMind (Farzad 🦅)
در این مقاله و مقاله جدیدی که در اومده
RAG
🔹
Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
🔹

✔️مدل های RAG، ساختار جدیدی برای مدل های Retrieval هستن که با knowledge سرو کار دارن و تلاش میکنند وقتی جنریت میکنن نالج محور باشن!
✔️ منظور از knowledge، هر دیتابیسی که شامل اطلاعاتی هستش مثل ویکی پدیا، البته فقط ویکی پدیا نیست لزوما
✔️ همونطور که گفتم این یک ساختار جدید هستش، Seq2Seq و نسبت به ساختار های E2E عادی و همچنین کاندیدا محور بهتر کار کرده.
✔️به خاطر محبوبیت و کاراییش، Huggingface هم این ساختار رو به کتابخونه ترنسفورمر ها اضافه کرده.
▪️

Introducing Self-RAG, a new easy-to-train, customizable, and powerful framework for making an LM learn to retrieve, generate, and critique its own outputs and retrieved passages, by using model-predicted reflection tokens.

📜 Self-RAG: Learning to Retrieve, Generate, and Critique through Self-Reflection
🌐 Project

#مقاله #ایده_جذاب #دیتاست

🔸 مطالب بیشتر 👇👇

✅ @AI_DeepMind
🔸 @AI_Person
▪️ @css_nlp
hottg.com/ai_python_arxiv/16066
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در این مقاله و مقاله جدیدی که در اومده

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