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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 News & Web3 Events | TON Ecosystem

@tonevents_en · Post #1290 · 02/27/2025, 10:44 AM

✉ xQuest — What's Next? 💬The Earn phase in xQuest Launch has officially ended. Over 125,000 users completed various quest tasks: from learning basic xRocket features to mastering trading and staking. This impressive result demonstrates high interest in the new platform. ⏺➕Now the Calculationphase is going, during which the campaign results will be summarize. 💰 After calculations, the Сlaim phase will begin – from March 3rd to March 10th, participants of the first xQuest campaign can claim their earned rewards and share the prize pool of 300,000 $XROCK (~$7750). Trade on xRocket exchange #xQuest#xRocket