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--- |
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language: da |
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tags: |
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- danish |
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- bert |
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- sentiment |
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- polarity |
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license: cc-by-4.0 |
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widget: |
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- text: "Sikke en dejlig dag det er i dag" |
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--- |
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# Danish BERT fine-tuned for Sentiment Analysis <img src="https://raw.githubusercontent.com/ebanalyse/NERDA/main/logo.png" align="right" height=150/> |
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This model detects polarity ('positive', 'neutral', 'negative') of danish texts. |
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It is trained and tested on Tweets annotated by [Alexandra Institute](https://github.com/alexandrainst). The model is trained with the [`senda`](https://github.com/ebanalyse/senda) package. |
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Here is an example of how to load the model in PyTorch using the [🤗Transformers](https://github.com/huggingface/transformers) library: |
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```python |
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from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline |
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tokenizer = AutoTokenizer.from_pretrained("pin/senda") |
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model = AutoModelForSequenceClassification.from_pretrained("pin/senda") |
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# create 'senda' sentiment analysis pipeline |
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senda_pipeline = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer) |
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text = "Sikke en dejlig dag det er i dag" |
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# 'what a lovely day' |
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senda_pipeline("Sikke en dejlig dag det er i dag") |
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``` |
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