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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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AI & Law

@ai_and_law · Post #746 · 01/20/2026, 08:04 AM

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🇨🇦AI Defamation Risk: Canadian Artist Prepares Lawsuit After Google Error Canadian musician Ashley MacIsaac says a Google AI-generated summary falsely labeled him a convicted sex offender, leading a concert venue to cancel his show. MacIsaac told the Canadian Press he believes the system confused him with another individual in Canada who has similar charges, but the error directly cost him income and harmed his reputation. MacIsaac is now preparing to sue Google, arguing that the misinformation amounts to defamation and created real-world risks, including potential issues at border controls. He stated that AI companies must be held accountable for what their systems publish and what harms they can reasonably prevent, noting that he is unlikely to be the last person affected by such errors. The incident underscores how AI-generated summaries can produce high-impact false statements about individuals, with immediate legal, economic, and personal consequences, even when no human editorial judgment is involved. #AI#AIDefamation#Liability#GenerativeAI#ReputationRisk

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