| --- |
| tags: |
| - xmod |
| - adapter-transformers |
| - adapterhub:eu/cc100 |
| language: |
| - eu |
| license: "mit" |
| --- |
| |
| # Adapter `AdapterHub/xmod-base-eu_ES` for AdapterHub/xmod-base |
| |
| An [adapter](https://adapterhub.ml) for the `AdapterHub/xmod-base` model that was trained on the [eu/cc100](https://adapterhub.ml/explore/eu/cc100/) dataset. |
| |
| This adapter was created for usage with the **[Adapters](https://github.com/Adapter-Hub/adapters)** library. |
| |
| ## Usage |
| |
| First, install `adapters`: |
| |
| ``` |
| pip install -U adapters |
| ``` |
| |
| Now, the adapter can be loaded and activated like this: |
| |
| ```python |
| from adapters import AutoAdapterModel |
| |
| model = AutoAdapterModel.from_pretrained("AdapterHub/xmod-base") |
| adapter_name = model.load_adapter("AdapterHub/xmod-base-eu_ES", source="hf", set_active=True) |
| ``` |
| |
| ## Architecture & Training |
| |
| This adapter was extracted from the original model checkpoint [facebook/xmod-base](https://huggingface.co/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 |
| |
| <!-- Add some description here --> |
| |
| ## Citation |
| |
| [Lifting the Curse of Multilinguality by Pre-training Modular Transformers (Pfeiffer et al., 2022)](http://dx.doi.org/10.18653/v1/2022.naacl-main.255) |
| |
| ``` |
| @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" |
| } |
| ``` |