model = AutoAdapterModel.from_pretrained("facebook/bart-base") config = AdapterConfig.load("pfeiffer", non_linearity="relu", reduction_factor=16) model.load_adapter("nli/rte@ukp", config=config)
{ "ln_after": false, "ln_before": false, "mh_adapter": false, "output_adapter": true, "adapter_residual_before_ln": false, "non_linearity": "relu", "original_ln_after": true, "original_ln_before": true, "reduction_factor": 16, "residual_before_ln": true }
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@misc{pfeiffer2020adapterfusion, title={AdapterFusion: Non-Destructive Task Composition for Transfer Learning}, author={Jonas Pfeiffer and Aishwarya Kamath and Andreas Rücklé and Kyunghyun Cho and Iryna Gurevych}, year={2020}, eprint={2005.00247}, archivePrefix={arXiv}, primaryClass={cs.CL} }
@inproceedings{bentivogli2009fifth, title={The Fifth PASCAL Recognizing Textual Entailment Challenge.}, author={Bentivogli, Luisa and Clark, Peter and Dagan, Ido and Giampiccolo, Danilo}, booktitle={TAC}, year={2009} }