#jupyter_notebook#ai#llm#llms#multi_modal#openai#python#rag
Retrieval-Augmented Generation (RAG) is a technique that helps improve the accuracy of large language models by fetching relevant information from databases or documents. This approach ensures that the model's responses are based on up-to-date and accurate data, reducing errors and "hallucinations" where the model might provide false information. For users, RAG offers more reliable and trustworthy responses, allowing them to verify the sources used to generate those responses. This method also saves resources by avoiding the need to retrain models with new data.
https://github.com/FareedKhan-dev/all-rag-techniques
RsS iS dEaD LOL: discover RSS Feeds of your follows on Mastodon
频道曾经提及过一个叫 FeedsMage 的服务,用于从你 fo 的推友的 Bio 里找链接,再从链接里找 Feed ,最后可生成一个 #OPML 文件。RsS iS dEaD LOL 则是长毛象版的 FeedsMage,从你 fo 的 Fediverse 用户的 Bio 里找链接,发现 RSS,然后可生成 #OPML:
https://rss-is-dead.lol/
例如我的:
https://rss-is-dead.lol/user?profileUrl=https%3A%2F%2Fmastodon.social%2Fusers%2FAboutRSS
发现于作者嘟文:
https://mastodon.social/@paulcuth/112178886374464145