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Source channel @githubtrending · Post #15432 · Jan 23

#jupyter_notebook#chinese_llm#chinese_nlp#finetune#generative_ai#instruct_gpt#instruction_set#llama#llm#lora#open_models#open_source#open_source_models#qlora AirLLM is a tool that lets you run very large AI models on computers with limited memory by using a smart layer-by-layer loading technique instead of traditional compression methods. You can run a 70-billion-parameter model on just 4GB of GPU memory, or even a 405-billion-parameter model on 8GB, without losing model quality. The benefit is that you can use powerful AI models on affordable hardware without expensive upgrades, and the tool also offers optional compression features that can speed up performance by up to 3 times while maintaining accuracy. https://github.com/lyogavin/airllm

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Amazing Geography 🌍

@amazingeo · Post #212 · 09/10/2025, 04:12 PM

🌍 Milan has over 3 million trees as part of its city plan, giving it more trees than people. Urban forests like this reduce heat, clean air, and boost well-being for city residents. ✨ #cities⚡#sustainability⚡#planning⚡#geography⚡#nature⚡#earth 👉subscribe Amazing Geography🌍 ​

Amazing Geography 🌍

@amazingeo · Post #104 · 08/23/2025, 08:12 PM

🌍 Hong Kong’s extensive network of elevated walkways—some stretching over 800 meters—lets people travel between major buildings without ever touching the street, maximizing space in the crowded city. ✨ #urban⚡#planning⚡#cityscape⚡#infrastructure⚡#geography⚡#nature⚡#earth 👉subscribe Amazing Geography🌍 ​

GitHub Trends

@githubtrending · Post #14639 · 04/27/2025, 01:00 PM

#python#agent_computer_interface#ai_agents#computer_automation#computer_use#grounding#gui_agents#in_context_reinforcement_learning#memory#mllm#planning#retrieval_augmented_generation Agent S2 is a smart AI assistant that handles computer tasks by breaking them into smaller steps and using specialized tools for each part, making it highly adaptable and efficient across different systems like Windows and Android. It outperforms other AI tools in completing complex tasks, learns from experience, and adjusts plans as needed, helping users automate digital work more reliably and effectively. https://github.com/simular-ai/Agent-S