QLoRA


Révision datée du 30 décembre 2023 à 09:37 par Pitpitt (discussion | contributions) (Page créée avec « ==en construction== == Définition == XXXXXXXXX == Français == ''' QLoRA ''' == Anglais == ''' QLoRA''' QLoRA stands for quantized LoRA (low-rank adaptation). The standard LoRA method modifies a pretrained LLM by adding low-rank matrices to the weights of the model's layers. These matrices are smaller and, therefore, require fewer resources to update during finetuning. In QLoRA, these low-rank matrices are quantized, meaning their numerical precision is... »)
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Définition

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QLoRA

Anglais

QLoRA

 QLoRA stands for quantized LoRA (low-rank adaptation). The standard LoRA method modifies a pretrained LLM by adding low-rank matrices to the weights of the model's layers. These matrices are smaller and, therefore, require fewer resources to update during finetuning.

In QLoRA, these low-rank matrices are quantized, meaning their numerical precision is reduced. This is done by mapping the continuous range of values in these matrices to a limited set of discrete levels. This process reduces the model's memory footprint and computational demands, as operations on lower-precision numbers are less memory-intensive.


Source : arxiv

Contributeurs: Patrick Drouin, wiki