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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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Host Testing and evaluation

@HostEvaluate · Post #707 · 12/29/2020, 06:42 AM

#US#LAX#Psychz#Dedicated Host Provider: Psychz Specification: E3-1230v2 (4C8T) | 16GB RAM | 2*1T Storage | Unmetered Transfer @ 1Gbps | $24 /month https://paste.ubuntu.com/p/xBB396QJ3N/ 到大陆薛定谔的路由,电信去程 163