deepset/xlm-roberta-base-squad2 is an open-weight multilingual transformer model fine-tuned for extractive question answering on SQuAD 2.0. Developers can download and run it locally with Python and Hugging Face tooling.
In the Foundation models & chat space, Xlm Roberta Base Squad2 takes a focused approach. It focuses on answering questions from supplied text across multiple languages without training a question-answering model from scratch. It is built as an open-source project for machine learning developers. The project is open source (Apache-2.0). Xlm Roberta Base Squad2 is available on the web and the command line, and it can be self-hosted.
deepset builds and maintains Xlm Roberta Base Squad2, and it first shipped in 2019. The project is developed in the open on GitHub with 26.2k stars and 717 commits in the last 90 days. Key capabilities include question answering, multilingual support, and SQuAD 2.0 fine-tuning.
Summary written by a language model from the project’s public pages.
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