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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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Libertà è ragione

@libertaeragione · Post #4455 · 03/11/2026, 11:11 AM

#Elezioni#Nepal Risultati definitivi: Affluenza: 58,07% (-3,34 rispetto al 2022, proporzionale) #RSP|Centro-sinistra: 182 seggi (+162 rispetto al 2022) #NC|Centro-sinistra: 38 (-51) #CPNUML|Sinistra: 25 (-53) #NCP|Sinistra radicale: 17 (-28) #SSP|Populisti per la democrazia di base: 7 (+7) #RPP|Destra monarchica indù: 5 (-9) Indipendenti: 1 (-2) #PSPN|Centro-sinistra federalista: 0 (-12) #JP|Sinistra del Terai: 0 (-12) #NWPP|Juche: 0 (-1) #RJ|Estrema sinistra anti-federalista: 0 (-1) Totale seggi: 275 Maggioranza: 138 In foto, la mappa del voto. @OsservatorioEsteri