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modifying ( W ) directly, the LoRA approach seeks to decompose ( Δ W ). This decomposition is a crucial step in reducing the computational overhead associated with fine-tuning large models. Traditional finetuning can be reimagined us above. Here W is frozen where as ΔW is trainable (Image by the