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深入理解三种PEFT方法:LoRA的低秩更新、QLoRA的4位量化与DoRA的幅度 ...
点击上方“Deephub Imba”,关注公众号,好文章不错过 !LLaMA、Mistral、Qwen这些大语言模型动辄数十亿参数,在自定义数据上全量微调代价极高:65B 模型光是 float16 就要消耗掉约 130GB ...
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