YAML Metadata
Warning:
empty or missing yaml metadata in repo card
(https://huggingface.co/docs/hub/model-cards#model-card-metadata)
XLM-Align
Improving Pretrained Cross-Lingual Language Models via Self-Labeled Word Alignment (ACL-2021, paper, github)
XLM-Align is a pretrained cross-lingual language model that supports 94 languages. See details in our paper.
Example
model = = AutoModel.from_pretrained("CZWin32768/xlm-align")
Evaluation Results
XTREME cross-lingual understanding tasks:
Model | POS | NER | XQuAD | MLQA | TyDiQA | XNLI | PAWS-X | Avg |
---|---|---|---|---|---|---|---|---|
XLM-R_base | 75.6 | 61.8 | 71.9 / 56.4 | 65.1 / 47.2 | 55.4 / 38.3 | 75.0 | 84.9 | 66.4 |
XLM-Align | 76.0 | 63.7 | 74.7 / 59.0 | 68.1 / 49.8 | 62.1 / 44.8 | 76.2 | 86.8 | 68.9 |
MD5
b9d214025837250ede2f69c9385f812c config.json
6005db708eb4bab5b85fa3976b9db85b pytorch_model.bin
bf25eb5120ad92ef5c7d8596b5dc4046 sentencepiece.bpe.model
eedbd60a7268b9fc45981b849664f747 tokenizer.json
About
Contact: [email protected]
BibTeX:
@article{xlmalign,
title={Improving Pretrained Cross-Lingual Language Models via Self-Labeled Word Alignment},
author={Zewen Chi and Li Dong and Bo Zheng and Shaohan Huang and Xian-Ling Mao and Heyan Huang and Furu Wei},
journal={arXiv preprint arXiv:2106.06381},
year={2021}
}
- 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.