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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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SpotOnChain | Announcement

@spotonchain · Post #627 · 12/27/2023, 01:51 AM

🚨 Early buyer 0x808 deposited 30K $AAVE ($3.08M) to #Coinbase and #OKX via #Cumberland at $102.7 ~4hrs ago. Notably, the whale used only 500K $USDC to buy 12.5M #LEND (later converted to 125K $AAVE) at $0.04 back in May 2020. And has only sold 30.9K $AAVE ($3.15M) via DEX, Coinbase, and OKX at $101.7 on avg so far. Current holding: 100K $AAVE ($10.2M). Estimated total profit: $12.85M! 👉 More details: https://platform.spotonchain.ai/en/signal-details/early-buyer-deposited-aave-to-exchanges-14545