model = AutoAdapterModel.from_pretrained("distilbert-base-uncased") config = AdapterConfig.load("pfeiffer") model.load_adapter("sentiment/rotten_tomatoes@ukp", config=config)
{ "ln_after": false, "ln_before": false, "mh_adapter": false, "output_adapter": true, "adapter_residual_before_ln": false, "non_linearity": null, "original_ln_after": true, "original_ln_before": true, "reduction_factor": null, "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{Pang+Lee:05a, author = {Bo Pang and Lillian Lee}, title = {Seeing stars: Exploiting class relationships for sentiment categorization with respect to rating scales}, year = {2005}, pages = {115--124}, booktitle = {Proceedings of ACL} }