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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 #65047 · 04/10/2026, 04:10 PM

🚀 Whop Introduces Treasury Yield Product Following Tether Investment Whop has launched its Treasury yield product on March 25, following a significant investment from Tether in February, which valued the company at $1.6 billion. According to NS3.AI, the product was introduced after Tether's $200 million investment. Steven Schwartz noted that 3% of users engaged with the beta version within a week, despite the absence of a marketing campaign. The product channels funds through a Veda vault on Plasma into Aave lending markets, offering an annual percentage yield (APY) of up to 6%. The investment from Tether will enable Whop to integrate on-platform USDT wallets and payment options. #Whop#Tether#TreasuryYield#Investment#Crypto#APY#Aave#USDT#Fintech#Blockchain#AAVE