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Source channel @githubtrending · Post #14993 · Jul 24
#jupyter_notebook Retrieval Augmented Generation (RAG) helps large language models (LLMs) answer questions using up-to-date or private information by connecting them to external data sources, unlike fine-tuning which retrains the model on specific data. RAG is useful when you need current, dynamic information without costly retraining, making it ideal for tasks like customer support or knowledge management. Fine-tuning is better for deep expertise in a specialized field but requires more data and effort. Using RAG lets you get accurate, relevant answers quickly by combining the model’s language skills with fresh, specific data, improving usefulness and reliability. https://github.com/langchain-ai/rag-from-scratch
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@gsbe_uz · Post #1243 · 03/12/2024, 01:12 PM
🇪🇸 Xalqaro biznes sohasida ekspert, ispaniyalik Romero de Marselo Adolfo tomonidan Oliy maktabning professor, o‘qituvchi va tinglovchilari uchun. 🇺🇿 “O‘zbekistonning kichik va o‘rta biznes kompaniyalari uchun Yevropa Ittifoqi bozoriga kirish va xalqaro biznes yuritish imkoniyatlari” mavzusida ma’ruzasidan video-reportaj. #GraduateSchool#GuestLecture#SME#Internalization Web-site | Telegram | Facebook | Instagram
@gsbe_uz · Post #1242 · 03/12/2024, 12:05 PM
Xalqaro biznes sohasidagi ekspert ishtirokida ochiq ma’ruza bo‘lib o‘tdi 🇺🇿UZB ___ Guest lecture was held with the participation of a leading expert in the field of international business 🇬🇧ENG ___ Состоялась гостевая лекция с участием ведущего эксперта в сфере международного бизнеса 🇷🇺RU #GraduateSchool#GuestLecture#SME#Internalization Web-site | Telegram | Facebook | Instagram