#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
Мой Говорящий Том 2
(My Talking Tom 2)
🆕Обновление
Возьмите навоспитание маленького котёнка и вырастите из него взрослого кота. Заботьтесь о своём виртуальном питомце: дайте ему имя, кормите его, играйте с ним и воспитывайте.
⚙️Мод на монеты и звезды. Пройдите игровое обучение и перезайдите в игру. Кэш встроен в установщик. #Tom
#Аркады@pm_plus
#Tom@pm_plus
📱Play Market +
⚡️ НАШ ЧАТ
M-m猫m和h老l鼠s- 猫和老鼠:雪人国大冒险 Tom and Jerry: Snowman's Land (2022)
直达链接:https://pan.quark.cn/s/a5cb74556dcc
#猫和老鼠:雪人国大冒险
#Tom and Jerry: Snowman's Land
#猫和老鼠之雪人乐园圣诞节
链接:https://link3.cc/sf_com
#电影#喜剧#美国#2022年代