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 # Multilingual mDeBERTa-v3-base-mnli-xnli
 ## Model description
 This multilingual model can perform natural language inference (NLI) on 100 languages and is therefore also suitable for multilingual zero-shot classification. The underlying model was pre-trained by Microsoft on the [CC100 multilingual dataset](https://huggingface.co/datasets/cc100). It was then fine-tuned on the [XNLI dataset](https://huggingface.co/datasets/xnli), which contains hypothesis-premise pairs from 15 languages, as well as the English [MNLI dataset](https://huggingface.co/datasets/multi_nli).
-As of December 2021, mDeBERTa-base is the best performing multilingual transformer (base) model, introduced by Microsoft in [this paper](https://arxiv.org/pdf/2111.09543.pdf). 
+As of December 2021, mDeBERTa-base is the best performing multilingual base-sized transformer model, introduced by Microsoft in [this paper](https://arxiv.org/pdf/2111.09543.pdf). 
 
 
 ## Intended uses & limitations