|
--- |
|
tags: |
|
- adapter-transformers |
|
- xmod |
|
- adapterhub:am/cc100 |
|
language: |
|
- am |
|
license: "mit" |
|
--- |
|
|
|
# Adapter `AdapterHub/xmod-base-am_ET` for AdapterHub/xmod-base |
|
|
|
An [adapter](https://adapterhub.ml) for the `AdapterHub/xmod-base` model that was trained on the [am/cc100](https://adapterhub.ml/explore/am/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-am_ET", 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" |
|
} |
|
``` |
