#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
#TIL – MILLAT KO‘RKI
21-oktyabr – o‘zbek tili bayrami kuni barchamizga muborak bo‘lsin!
O‘zlikni anglash, milliy ong va tafakkurning ifodasi, avlodlar o‘rtasidagi ruhiy-ma’naviy bog‘liqlik til orqali namoyon bo‘ladi. Jamiki ezgu fazilatlar inson qalbiga, avvalo, ona allasi, ona tilining betakror jozibasi bilan singadi.
Ona tili – bu millatning ruhidir.
Sizlarni yurtimiz tarixidagi muhim sanalardan biri – O‘zbek tili bayrami kuni bilan chin qalbdan muborakbod etamiz!
Ushbu ulug‘ bayram barchamizga quvonch, faxr va g‘urur ulashsin! Ona tilimiz abadiy yashasin, doimo barhayot bo‘lsin!
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#TIL there are laws mandate the use of a specific font.
[... A]ny text that is displayed on a primary package or secondary package, or on any overwrap covering the package, must [...] be printed in a regular weight and width Lucida Sans Serif font style, without italics, and in gray.
https://gazette.gc.ca/rp-pr/p2/2019/2019-05-01/html/sor-dors107-eng.html🐟