language: multilingual en ar bg de el es fr hi ru sw th tr ur vi zh license: mit tags: zero shot classification text classification nli pytorch metrics: accuracy datasets: multi nli xnli pipeline tag: zero shot classification widget: text: "Angela Merkel ist eine Politikerin in Deutschland und Vorsitzende der CDU" candidate labels: "politics, economy, entertainment, environment" Multilingual MiniLMv2 L6 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 multilingual MiniLM L6 model was created by Microsoft and was distilled from XLM RoBERTa large (see details in the original paper and newer information in this repo). The model was then fine tuned on the XNLI dataset, which contains hypothesis premise pairs from 15 languages, as well as the English MNLI dataset. The main advantage of distilled models is that they are smaller (faster inference, lower memory requirements) than their teachers (XLM RoBERTa large). The disadvantage is that they lose some of the performance of their larger teachers. For highest inference speed, I recommen…
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