Comments (2)
While our current model is trained with English data only, but we found our v2 model has reasonable good performance on several subtasks(i.e. zh, fr, de, es) from XNLI. You may take a try. We are also planning to make a multi-lingual version in near future.
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any update?
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Related Issues (20)
- No module named 'torch._six' HOT 2
- AssertionError: RTD is not registed. HOT 1
- n/a
- Deberta-v3-base Generator model HOT 2
- Load deberta-v3-large but got deberta-v2 model HOT 2
- Install fails due to use of deprecated `sklearn` package
- Eligibility for Commercial Use HOT 1
- When calculating Qr, why is the W of content used instead of the W of position used?
- Trying to run rtd_task.py on Windows HOT 1
- EOF error while running the rtd.sh script HOT 1
- Trying to initialize model "large"
- Question regarding symmetric KL Loss
- Model is not initialized correctly when path to a pretrained model is provided via `pre_trained`
- Inference gives different results when using multiple gpus (distributed mode) vs just one gpu (not distributed mode)
- No assert: Training does not start when using different tokenizer/ tokenized-data
- Reason for missing values in table for the Roberta-base, mrpc entry
- How can I evaluate COPA dataset?
- Fine-tune DeBERTa v3 language model, worthwhile endeavour? HOT 5
- Generator weights
- Pretraining the deberta-v3 by larger context length.
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