An open-weight multilingual transformer model for zero-shot text classification and natural language inference. Developers can download the model or run it through hosted inference services in applications that classify text without task-specific training.
Multilingual MiniLMv2 L12 Mnli Xnli is an Other AI project. It focuses on classifying multilingual text without training a separate supervised model for each category. Multilingual MiniLMv2 L12 Mnli Xnli is an open-source project aimed at machine learning developers. The project is open source (MIT). Multilingual MiniLMv2 L12 Mnli Xnli is available on the web and API.
It is developed by Moritz Laurer, and it first shipped in 2019. The project is developed in the open on GitHub with 22.2k stars. Key capabilities include zero-shot classification, multilingual inference, and natural language inference. It exposes integrations via a public API.
Summary written by a language model from the project’s public pages.
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