metadata
tags:
- adapter-transformers
- xlm-roberta
datasets:
- UKPLab/m2qa
Adapter AdapterHub/m2qa-xlm-roberta-base-mad-x-domain-qa-head
for xlm-roberta-base
An adapter for the xlm-roberta-base
model that was trained on the UKPLab/m2qa dataset and includes a prediction head for question answering.
This adapter was created for usage with the adapter-transformers library.
Usage
First, install adapter-transformers
:
pip install -U adapter-transformers
Note: adapter-transformers is a fork of transformers that acts as a drop-in replacement with adapter support. More
Now, the adapter can be loaded and activated like this:
from transformers import AutoAdapterModel
model = AutoAdapterModel.from_pretrained("xlm-roberta-base")
adapter_name = model.load_adapter("AdapterHub/m2qa-xlm-roberta-base-mad-x-domain-qa-head", source="hf", set_active=True)
Architecture & Training
See our repository for more information: See https://github.com/UKPLab/m2qa/tree/main/Experiments/mad-x-domain
Evaluation results
Citation
@article{englaender-etal-2024-m2qa,
title="M2QA: Multi-domain Multilingual Question Answering",
author={Engl{\"a}nder, Leon and
Sterz, Hannah and
Poth, Clifton and
Pfeiffer, Jonas and
Kuznetsov, Ilia and
Gurevych, Iryna},
journal={arXiv preprint},
url="https://arxiv.org/abs/2407.01091",
month = jul,
year="2024"
}