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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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Libreware

@libreware · Post #957 · 06/22/2021, 01:28 PM

— LibreCellular 21.04 documentation –https://librecellular.org/ The LibreCellular project aims to make it easier to create #4G cellular #networks with open source software and low cost software-defined radio (#SDR) hardware. Seeking to achieve this via validated hardware and software configurations that are subjected to rigorous testing, together with additional tooling and #documentation for repeatable deployment. LibreCellular will build on the work of numerous existing open source software and hardware projects, related to both the #cellular platform itself and associated test #infrastructure. Where necessary additional components will be developed, with any software source code and #hardware designs published under #opensource licences. The focus is very much on integration, testing, packaging and documentation, reusing and building upon existing solutions.. #LibreCellular#CellulaireLibre