Multilingual XLM RoBERTa large for Extractive QA on various languages Overview Language model: xlm roberta large Language: Multilingual Downstream task: Extractive QA Training data: SQuAD 2.0 Eval data: SQuAD dev set German MLQA German XQuAD Training run: MLFlow link Code: See an example extractive QA pipeline built with Haystack Infrastructure : 4x Tesla v100 Hyperparameters Usage In Haystack Haystack is an AI orchestration framework to build customizable, production ready LLM applications. You can use this model in Haystack to do extractive question answering on documents. To load and run the model with Haystack: For a complete example with an extractive question answering pipeline that scales over many documents, check out the corresponding Haystack tutorial. In Transformers Performance Evaluated on the SQuAD 2.0 English dev set with the official eval script. Evaluated on German MLQA: test context de question de.json Evaluated on German XQuAD: xquad.de.json Usage In Haystack For doing QA at scale (i.e. many docs instead of single paragraph), you can load the model also in haystack: In Transformers Authors Branden Chan: branden.chan@deepset.ai Timo Möller: timo.moeller@deepset.ai…
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