Instructions to use microsoft/deberta-xlarge-v2 with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use microsoft/deberta-xlarge-v2 with Transformers:
# pip install -U transformers accelerate # Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("microsoft/deberta-xlarge-v2", device_map="auto") - Notebooks
- Google Colab
- Kaggle
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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 with 24 layers, 1536 hidden size. Total parameters 900M.
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#### Fine-tuning on NLU tasks
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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 with 24 layers, 1536 hidden size. Total parameters 900M. It's trained with 160GB data.
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#### Fine-tuning on NLU tasks
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