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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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Crypto M - Crypto News

@CryptoM · Post #65256 · 04/12/2026, 10:58 AM

🚀 RAVE Token Movement Sparks Interest Among Investors Analyst @ai_9684xtpa posted on X about a notable transaction involving the RAVE token. An investor, identified as @EnHeng456 enai.bnb, purchased 46,336.76 RAVE tokens at an average price of $0.4556 on the second day of its launch. The tokens were held until 48 days ago, when they were transferred to Aster at a price of $0.39 per token, with the purpose of the transfer remaining unclear. Recently, 41,025 tokens were moved from Aster, making the investor one of the top nine holders on the BSC network. If the tokens had not been sold, the investor's return rate would have reached 462%, with an unrealized profit of $86,000. #RAVE#TokenMovement#Investors#BSC#Transaction#Aster#Crypto#Blockchain#Investment#ReturnRate#UnrealizedProfit#X