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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 #1554 · 02/22/2026, 03:26 PM

The Internet, Reinvented. In this video, I build a #Reticulum#RNode and prove that completely different radios — #LoRa and Wi-Fi — can communicate through a hardware-agnostic networking stack. Reticulum routes traffic above the radio layer, automatically bridging dissimilar frequencies, interfaces, and modulation types. I then run it over Wi-Fi HaLow Haven nodes to create a long-range, encrypted IP #mesh with no traditional infrastructure. Finally, I push it further by running #ATAK across the network, demonstrating a fully open-source, decentralized communication stack in action. Checkout https://rmap.world/ You can install rnode software on your esp32/nrf52 based meshtastic/meshcore hardware