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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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djangoproject

@djangoproject · Post #433 · 09/07/2017, 11:11 AM

https://docs.python.org/3/library/gettext.html The #gettext module provides internationalization (#I18N) and localization (#L10N) services for your #Python modules and applications. It supports both the #GNU gettext message catalog #API and a higher level, class-based API that may be more appropriate for Python files. The interface described below allows you to write your module and application messages in one natural #language, and provide a catalog of #translated messages for running under different natural languages. Some hints on localizing your Python modules and applications are also given.