Instructions to use microsoft/deberta-v2-xlarge with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/deberta-v2-xlarge with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="microsoft/deberta-v2-xlarge")# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/deberta-v2-xlarge", device_map="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -46,7 +46,7 @@ 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={
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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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``` 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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