Instructions to use microsoft/mdeberta-v3-base with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/mdeberta-v3-base with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("fill-mask", model="microsoft/mdeberta-v3-base")# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/mdeberta-v3-base", dtype="auto") - Inference
- Notebooks
- Google Colab
- Kaggle
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README.md
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@@ -28,7 +28,7 @@ We present the dev results on XNLI with zero-shot crosslingual transfer setting,
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| Model |avg | en | fr| es | de | el | bg | ru |tr |ar |vi | th | zh | hi | sw | ur |
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| XLM-R-base |75.6 |85.8|79.7|80.7 |78.7 |77.5 |79.6 |78.1 |74.2 |73.8 |76.5 |74.6 |76.7| 72.4| 66.5| 68.3|
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| mDeBERTa-base|**79.8**+/-0.2|88.2|82.6|84.4 |82.7 |82.3 |82.4 |80.8 |79.5 |78.5 |78.1 |76.4 |79.5| 75.9| 73.9| 72.4|
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#### Fine-tuning with HF transformers
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| Model |avg | en | fr| es | de | el | bg | ru |tr |ar |vi | th | zh | hi | sw | ur |
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| XLM-R-base |75.6 |85.8|79.7|80.7 |78.7 |77.5 |79.6 |78.1 |74.2 |73.8 |76.5 |74.6 |76.7| 72.4| 66.5| 68.3|
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| mDeBERTa-base|**79.8**+/-0.2|**88.2**|**82.6**|**84.4** |**82.7** |**82.3** |**82.4** |**80.8** |**79.5** |**78.5** |**78.1** |**76.4** |**79.5**| **75.9**| **73.9**| **72.4**|
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#### Fine-tuning with HF transformers
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