model = AutoAdapterModel.from_pretrained("bert-base-multilingual-cased")
config = AdapterConfig.load("pfeiffer", non_linearity="relu", reduction_factor=2)
model.load_adapter("cdo/wiki@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": 2,
"residual_before_ln": true
}
| Identifier | Comment | Score | Download |
|---|---|---|---|
| madx DEFAULT |
@article{pfeiffer20madx,
title={{MAD-X}: An {A}dapter-based {F}ramework for {M}ulti-task {C}ross-lingual {T}ransfer},
author={Pfeiffer, Jonas and Vuli\'{c}, Ivan and Gurevych, Iryna and Ruder, Sebastian},
journal={arXiv preprint},
year={2020},
url={https://arxiv.org/pdf/2005.00052.pdf},
}
@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}
}