LoReFT: Representation Finetuning for Language Models

Parameter-efficient fine-tuning or PeFT methods seek to adapt large language models via updates to a small number of weights. However, a majority of existing interpretability work has demonstrated that representations encode semantic rich information, suggesting that it might be a better and more powerful alternative to edit these representations. Pre-trained large models are often fine […]

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