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Corrected link to paper (#6905)
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@ -4,7 +4,7 @@ This model was trained for sentiment classification of German language texts. To
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we provide a Python package that bundles the code need for the preprocessing and inferencing.
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The model uses the Googles Bert architecture and was trained on 1.834 million German-language samples. The training data contains texts from various domains like Twitter, Facebook and movie, app and hotel reviews.
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You can find more information about the dataset and the training process in the [paper](http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.201.pdf).
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You can find more information about the dataset and the training process in the [paper](http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.202.pdf).
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## Using the Python package
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