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--- |
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language: |
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- de |
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tags: |
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- deepset/gbert-large |
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--- |
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#German Sentiment Analysis |
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This model predicts sentiment for German text. |
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#Usage |
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First set up the model: |
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```python |
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# if necessary: |
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# !pip install transformers |
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from transformers import pipeline |
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sentiment_model = pipeline(model="aari1995/German_Sentiment") |
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``` |
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to use it: |
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```python |
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sentence = ["Ich liebe die Bahn. Pünktlich wie immer ... -.-","Krasser Service"] |
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result = sentiment_model(sentence) |
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print(result) |
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#Output: |
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#[{'label': 'negative', 'score': 0.4935680031776428},{'label': 'positive', 'score': 0.5790663957595825}] |
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``` |
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#Credits / Special Thanks: |
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This model was fine-tuned by Aaron Chibb. It is trained on [twitter dataset by tygiangz](https://huggingface.co/datasets/tyqiangz/multilingual-sentiments) and based on gBERT-large by [deepset](https://huggingface.co/deepset/gbert-large). |
