Adapter AdapterHub/xmod-base-eo_EO for AdapterHub/xmod-base

An adapter for the AdapterHub/xmod-base model that was trained on the eo/cc100 dataset.

This adapter was created for usage with the Adapters library.

Usage

First, install adapters:

pip install -U adapters

Now, the adapter can be loaded and activated like this:

from adapters import AutoAdapterModel

model = AutoAdapterModel.from_pretrained("AdapterHub/xmod-base")
adapter_name = model.load_adapter("AdapterHub/xmod-base-eo_EO", source="hf", set_active=True)

Architecture & Training

This adapter was extracted from the original model checkpoint facebook/xmod-base to allow loading it independently via the Adapters library. For more information on architecture and training, please refer to the original model card.

Evaluation results

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Citation

Lifting the Curse of Multilinguality by Pre-training Modular Transformers (Pfeiffer et al., 2022)

@inproceedings{pfeiffer-etal-2022-lifting,
    title = "Lifting the Curse of Multilinguality by Pre-training Modular Transformers",
    author = "Pfeiffer, Jonas  and
      Goyal, Naman  and
      Lin, Xi  and
      Li, Xian  and
      Cross, James  and
      Riedel, Sebastian  and
      Artetxe, Mikel",
    booktitle = "Proceedings of the 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
    month = jul,
    year = "2022",
    address = "Seattle, United States",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2022.naacl-main.255",
    doi = "10.18653/v1/2022.naacl-main.255",
    pages = "3479--3495"
}