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Source channel @githubtrending · Post #14815 · Jun 10

#jupyter_notebook#chatglm#chatglm3#gemma_2b_it#glm_4#internlm2#llama3#llm#lora#minicpm#q_wen#qwen#qwen1_5#qwen2 This guide helps beginners set up and use open-source large language models (LLMs) on Linux or cloud platforms like AutoDL, with step-by-step instructions for environment setup, model deployment, and fine-tuning for models such as LLaMA, ChatGLM, and InternLM[2][4][5]. It covers everything from basic installation to advanced techniques like LoRA and distributed fine-tuning, and supports integration with tools like LangChain and online demo deployment. The main benefit is making powerful AI models accessible and easy to use for students, researchers, and anyone interested in experimenting with or customizing LLMs for their own projects[2][4][5]. https://github.com/datawhalechina/self-llm

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@kejiqu · Post #4272 · 03/19/2026, 01:39 AM

2026 图灵奖授予量子密码学发明者 计算机协会 (Association for Computing Machinery) 于周三宣布,Charles Bennett 博士和 Gilles Brassard 博士因其在量子密码学及相关技术方面的开创性工作而共同荣获 2026 年图灵奖。该奖项通常被称为计算机领域的诺贝尔奖,奖金为 100 万美元。两位科学家于 1983 年发表研究,证明了量子地铁票无法伪造,并于 1984 年提出了 BB84 系统,该系统利用光子创建加密密钥,通过量子力学原理实现安全加密。Slashdot 🏷#Turing#Award#Quantum#Cryptography#BB84 📢频道👥群组📝投稿