XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models
converted checkpoint of XLM-V from fairseq to huggingface
Fairseq
if original model is needed, please check, model checkpoint:
https://dl.fbaipublicfiles.com/fairseq/xlmv/xlmv.base.tar.gz
and how to use it
https://github.com/facebookresearch/fairseq/blob/main/examples/xlmr/README.md
Note: please use official checkpoints, if they will be added to transformers (this repo is for personal usage/experiments)
Citation
@misc{https://doi.org/10.48550/arxiv.2301.10472,
doi = {10.48550/ARXIV.2301.10472},
url = {https://arxiv.org/abs/2301.10472},
author = {Liang, Davis and Gonen, Hila and Mao, Yuning and Hou, Rui and Goyal, Naman and Ghazvininejad, Marjan and Zettlemoyer, Luke and Khabsa, Madian},
keywords = {Computation and Language (cs.CL), Machine Learning (cs.LG), FOS: Computer and information sciences, FOS: Computer and information sciences},
title = {XLM-V: Overcoming the Vocabulary Bottleneck in Multilingual Masked Language Models},
publisher = {arXiv},
year = {2023},
copyright = {Creative Commons Attribution Share Alike 4.0 International}
}
- Downloads last month
- 3
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.