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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 #435 · 09/07/2017, 01:47 PM

https://www.python.org/dev/peps/pep-0498/ #Interpolation # Python supports multiple ways to format text strings. # These include %-formatting, # str.format(), # and string.Template # The !s, !r, and !a conversions are not strictly required. # Because arbitrary expressions are allowed inside the #f_strings, # this code: »> a = 'some string' »> f'{a!r}' "'some string'" Is identical to: »> f'{repr(a)}' "'some string'" Similarly, !s can be replaced by calls to #str() and !a by calls to #ascii().

djangoproject

@djangoproject · Post #513 · 11/30/2017, 10:00 PM

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