#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
#headset
#rapoo
Rapoo VH350S RGB
😎Виртуальный 7.1 Surround Sound – эффект полного погружения
😎40 мм драйверы – мощные басы и четкий звук
😎ENC-микрофон – голос без шумов в любой ситуации
😎RGB-подсветка – стиль и атмосфера гейминга
😎Эргономика – мягкие амбушюры + металлическое оголовье
😎USB-подключение, кабель 2.4 м – удобно и надежно
😎Лёгкий вес ~358 г – комфорт при длительной игре
😎Играй дольше, слыши больше, побеждай с Rapoo!
😎20$
➖
➖
➖
➖
➖
➖
➖
➖
➖
➖
😎 +998338082030
😎@cyberwarriorboy
➖
➖
➖
➖
➖
➖
➖
➖
➖
➖
🔵Telegram📷Instagram🟥Youtube