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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
Search: #insert
@djangoproject · Post #428 · 08/30/2017, 03:40 AM
How #Django knows to #UPDATE vs. #INSERT when you call #save (), #Django follows this algorithm: If the object’s primary key attribute is set to a value that evaluates to True (i.e., a value other than None or the empty string), Django executes an UPDATE. If the object’s primary key attribute is not set or if the UPDATE didn’t update anything, Django executes an INSERT.