From 7420447fdfdc08d2cfcdc1cf2f3a8095306b9359 Mon Sep 17 00:00:00 2001 From: Moritz Laurer Date: Tue, 14 Feb 2023 12:51:03 +0000 Subject: [PATCH] Update README.md --- README.md | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index c5107ad..39f3f1f 100644 --- a/README.md +++ b/README.md @@ -34,9 +34,14 @@ widget: --- # 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 base-sized transformer model, introduced by Microsoft in [this paper](https://arxiv.org/pdf/2111.09543.pdf). +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 base-sized transformer model, +introduced by Microsoft in [this paper](https://arxiv.org/pdf/2111.09543.pdf). +If you are looking for a smaller, faster (but less performant) model, you can +try [multilingual-MiniLMv2-L6-mnli-xnli](https://huggingface.co/MoritzLaurer/multilingual-MiniLMv2-L6-mnli-xnli). ### How to use the model #### Simple zero-shot classification pipeline