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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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😂👉Вышел Новый Open source и пипец какой мощный го тестить! Цены $0.04 per second for 1080p, $0.08 per second for 1440p $0.16 per second for 2160p 10 sec 4к 50 fps со звуком это лютая лють) Формат можно прописывать в ручную #fal | AcidCrunch

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Host Testing and evaluation

@HostEvaluate · Post #831 · 09/26/2022, 04:39 AM

#AEZA#DE#FAL Host Provider: AEZA Location: Falkenstein, Germany (Combahton) Specification: 1vCore(Ryzen 5950X) | 2GB RAM | 30G NVMe | Unmetered @ 1Gbps | €6.18 / Mo Looking Glass: lg.aeza.net 购买地址 感觉不如直接去买 Hetzner 的公有云或者 OLVPS 法兰克福。顺便吐槽一嘴,他们家 LG 真难用,做 traceroute 主机名也不显示。联通回程 telia, 电信 retn, 移动 de-cix. https://paste.red/p/04b35c727b10

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