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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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#jupyter_notebook #chinese_llm #chinese_nlp #finetune #generative_ai #instruct_gpt #instruction_set #llama #llm #lora #open_models #open_source #open_source_models #qlora

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@githubtrending · Post #14929 · 07/08/2025, 01:00 PM

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#swift#ci#cli#generator#specification#swift#xcode#xcodeproj#xcodeproject#yaml XcodeGen is a Swift command-line tool that automatically creates your Xcode project based on your folder structure and a simple YAML or JSON configuration file. This means you don’t have to manually manage your Xcode project files, avoiding merge conflicts in Git and keeping your project files always in sync with your folders. It supports complex setups, multiple targets, build settings, and schemes, and works well with CI systems. Using XcodeGen saves you time, reduces errors, and makes collaboration easier by letting you generate and update projects on demand without opening Xcode manually. This helps you focus more on coding and less on project setup. https://github.com/yonaskolb/XcodeGen

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#swift #ci #cli #generator #specification #xcode #xcodeproj #xcodeproject #yaml