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Изворен канал @pythonotes · Post #344 · 4 окт.

⭐️ Встречаем релиз 3.12 Из того что мне приглянулось: ▫️ Всё ближе sub-interpreters, на С уже можно пробовать. В Python-коде будет в следующем релизе. ▫️ Наконец закончится возня с кавычками в f-string ▫️ Говорят, хорошо ускорили async код. ➡️ Остальные подробности читаем здесь #release

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@githubtrending · Post #14815 · 10.06.2025 г., 11:30

#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