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@@ -17,7 +17,7 @@ pipeline_tag: zero-shot-classification
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- - text: "Ich habe ein Problem mit meinem Iphone das so schnell wie möglich gelöst werden muss."
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  candidate_labels: "Computer, Handy, Tablet, dringend, nicht dringend"
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  DESCRIPTION GOES HERE:
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  Satz 1:
 
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+ - text: "Ich habe ein Problem mit meinem Iphone, das so schnell wie möglich gelöst werden muss."
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  candidate_labels: "Computer, Handy, Tablet, dringend, nicht dringend"
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+ # SVALabs - Gbert Large Zeroshot Nli
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+ In this repository, we present our german zeroshot model.
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+ This model was trained on the basis of the German BERT large model from [deepset.ai](https://huggingface.co/deepset/gbert-large) and finetuned as a cross-encoder for Passage Retrieval using the [sentence-transformers](https://github.com/UKPLab/sentence-transformers) package.
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+ For this purpose, we translated the [MSMARCO-Passage-Ranking](https://github.com/microsoft/MSMARCO-Passage-Ranking) dataset using the [fairseq-wmt19-en-de](https://github.com/pytorch/fairseq/tree/master/examples/wmt19) translation model.
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+ ### Model Details
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+ | | Description or Link |
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+ |---|---|
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+ |**Base model** | [```german-nlp-group/electra-base-german-uncased```](https://huggingface.co/german-nlp-group/electra-base-german-uncased) |
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+ |**Finetuning task**| Passage Retrieval / Semantic Search |
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+ |**Source dataset**| [```MSMARCO-Passage-Ranking```](https://github.com/microsoft/MSMARCO-Passage-Ranking) |
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+ |**Translation model**| [```fairseq-wmt19-en-de```](https://github.com/pytorch/fairseq/tree/master/examples/wmt19) |
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  DESCRIPTION GOES HERE:
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  Satz 1: