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README.md
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- **Limitations**: The model is only train and tested on the German language, but can handle the other 8 languages with lower accuracy.
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## How to Use
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To use this model, you need to install the Hugging Face Transformers library and PyTorch. You can do this using pip:
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```bash
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This model was developed by Sary Nasser at HTW-Berlin under supervision of Martin Steinicke.
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## References
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- Oliver Guhr Dataset paper: [Training a Broad-Coverage German Sentiment Classification Model for Dialog
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Systems](http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.202.pdf)
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- Model architecture: [XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond
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- **Limitations**: The model is only train and tested on the German language, but can handle the other 8 languages with lower accuracy.
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## How to Use
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I have developed Python desktop application for the inference at my [repository](https://github.com/ssary/German-Sentiment-Analysis).
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To use this model, you need to install the Hugging Face Transformers library and PyTorch. You can do this using pip:
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```bash
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This model was developed by Sary Nasser at HTW-Berlin under supervision of Martin Steinicke.
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## References
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- Model's GitHub repository: [https://github.com/ssary/German-Sentiment-Analysis](https://github.com/ssary/German-Sentiment-Analysis)
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- Oliver Guhr Dataset paper: [Training a Broad-Coverage German Sentiment Classification Model for Dialog
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Systems](http://www.lrec-conf.org/proceedings/lrec2020/pdf/2020.lrec-1.202.pdf)
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- Model architecture: [XLM-T: Multilingual Language Models in Twitter for Sentiment Analysis and Beyond
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