# I am the Watcher. I am your guide through this vast new twtiverse.
#
# Usage:
# https://watcher.sour.is/api/plain/users View list of users and latest twt date.
# https://watcher.sour.is/api/plain/twt View all twts.
# https://watcher.sour.is/api/plain/mentions?uri=:uri View all mentions for uri.
# https://watcher.sour.is/api/plain/conv/:hash View all twts for a conversation subject.
#
# Options:
# uri Filter to show a specific users twts.
# offset Start index for quey.
# limit Count of items to return (going back in time).
#
# twt range = 1 1
# self = https://watcher.sour.is/conv/rxxub7q
構建 LLM 應用：句子 Transformer（第三部分）**
作者：Vipra Singh 編譯：ronghuaiyang 導讀通過檢索增強生成（RAG）應用的視角來學習大型語言模型（LLM）。在前幾篇博文中，我們學習了面向 RAG 的數據準備，這包括數據攝入、數據預處理及分塊。由於在執行 RAG 期間需要搜索相關的上下文分塊，我們必須將數據從文本格式轉換爲向量嵌入。因此，我們將探索使用 Sentence Transformers 來轉換文本的最 ⌘ Read more