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## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
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[DeBERTa](https://
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Please check the [official repository](https://github.com/microsoft/DeBERTa) for more details and updates.
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This the DeBERTa V2 xlarge model fine-tuned with MNLI task, 24 layers, 1536 hidden size. Total parameters 900M.
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## This model is deprecated, please use [DeBERTa-V2-XLarge-MNLI](https://huggingface.co/microsoft/deberta-v2-xlarge-mnli)
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### Citation
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If you find DeBERTa useful for your work, please cite the following paper:
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``` latex
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@inproceedings{
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he2021deberta,
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title={DEBERTA: DECODING-ENHANCED BERT WITH DISENTANGLED ATTENTION},
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author={Pengcheng He and Xiaodong Liu and Jianfeng Gao and Weizhu Chen},
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booktitle={International Conference on Learning Representations},
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year={2021},
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url={https://openreview.net/forum?id=XPZIaotutsD}
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}
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```
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## DeBERTa: Decoding-enhanced BERT with Disentangled Attention
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## This model is DEPRECATED, please use [DeBERTa-V2-XLarge-MNLI](https://huggingface.co/microsoft/deberta-v2-xlarge-mnli)
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