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mDeBERTa-v3-base-xnli-multilingual-nli-2mil7

MoritzLaurer · mDeBERTa-v3-base-xnli-multilingual-nli-2mil7

This multilingual model can perform natural language inference (NLI) on 100 languages and is therefore also suitable for multilingual zero-shot classification. The underlying mDeBERTa-v3-base model was pre-trained by Microsoft on the CC100 multilingual dataset with 100 languages. The model was then fine-tuned on the XNLI dataset and on the multilingual-NLI-26lang-2mil7 dataset. Both datasets contain more than 2.7 million hypothesis-premise pairs in 27 languages spoken by more than 4 billion people. As of December 2021, mDeBERTa-v3-base is the best performing multilingual base-sized transformer model introduced by Microsoft in this paper. This model was trained on the multilingual-nli-26lang-2mil7 dataset and the XNLI validation dataset.

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档案更新时间2026/11/2 19:16:26
OVERVIEW

模型介绍

This multilingual model can perform natural language inference (NLI) on 100 languages and is therefore also suitable for multilingual zero-shot classification. The underlying mDeBERTa-v3-base model was pre-trained by Microsoft on the CC100 multilingual dataset with 100 languages. The model was then fine-tuned on the XNLI dataset and on the multilingual-NLI-26lang-2mil7 dataset. Both datasets contain more than 2.7 million hypothesis-premise pairs in 27 languages spoken by more than 4 billion people. As of December 2021, mDeBERTa-v3-base is the best performing multilingual base-sized transformer model introduced by Microsoft in this paper. This model was trained on the multilingual-nli-26lang-2mil7 dataset and the XNLI validation dataset.

主要特点

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局限与注意事项

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PRICING & COST

来源报价与费用分析

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INDEPENDENT BENCHMARKS

公开评测与运行配置

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常见问题

开放权重是否代表可以免费商用?

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资料来源与可追溯记录

许可证:mit。模型介绍与第三方评测均以原来源的具体版本和方法为准。