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Source channel @olddriverGDstudy · Post #9 · Mar 17

#语录 凡哥语录 也许大家会觉得这里规矩多,甚至去年我还听说别人评价我们这是集中营,可是到头来,所谓“自由”的那些群如今一个个都凉了,只有我们健康持续的发展着,大队就是个平台,平台是属于大家的,我们就是帮你们维持好正常运营,别的真没多想,其实你们扪心自问,应该也有个中肯的评价吧 你这不够推拉,不能这么舔,你要说,我考虑一下,看你表现,下次给你准备点小惊喜 找女朋友炮友什么的,不能一味舔狗,要调动妹子的注意力和心情,不是说要pua人家,但是人pua不也是强调以我为主,讲究拉扯么,这个也一样的呀,当然啦,面对🐔还是给钱实在点,别整那些有的没的

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​​Совсем лайтовая статья для новичков "10 главных конструкций языка R". Содержание: - Комментарии - Переменные и векторы - Внешние модули - Ввод и вывод - Присваивание и сравнение - Условный оператор if - Цикл for - Функции - Классы, методы и объекты #статьи #easy

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@githubtrending · Post #15433 · 01/23/2026, 02:30 PM

#python#deepseek#demo#easy#embedding#flask#gpt#huggingface_transformers#llm#mcp#multimodal#openai#qwen#rag#sentence_transformers#ui#vllm#vlm UltraRAG is a lightweight framework that makes building retrieval-augmented generation (RAG) systems simple and fast. It uses a low-code approach where you write just dozens of lines of YAML configuration instead of complex code to create sophisticated AI workflows with conditional logic and loops. The framework includes a visual development environment where you can drag-and-drop to build pipelines, adjust parameters in real-time, and instantly convert your logic into interactive chat applications. This means you can deploy powerful AI systems that ground answers in your own data—reducing hallucinations and improving accuracy—without needing extensive coding expertise or lengthy development cycles. https://github.com/OpenBMB/UltraRAG