| language: da | |
| tags: | |
| - danish | |
| - bert | |
| - sentiment | |
| - polarity | |
| license: cc-by-4.0 | |
| widget: | |
| - text: "Sikke en dejlig dag det er i dag" | |
| # Danish BERT fine-tuned for Sentiment Analysis with `senda` | |
| This model detects polarity ('positive', 'neutral', 'negative') of danish texts. | |
| 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. | |
| Here is an example of how to load the model in PyTorch using the [🤗Transformers](https://github.com/huggingface/transformers) library: | |
| ```python | |
| from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline | |
| tokenizer = AutoTokenizer.from_pretrained("pin/senda") | |
| model = AutoModelForSequenceClassification.from_pretrained("pin/senda") | |
| # create 'senda' sentiment analysis pipeline | |
| senda_pipeline = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer) | |
| text = "Sikke en dejlig dag det er i dag" | |
| # 'what a lovely day' | |
| senda_pipeline("Sikke en dejlig dag det er i dag") | |
| ``` | |
| #### Contact | |
| Feel free to contact author Lars Kjeldgaard on [lars.kjeldgaard@eb.dk](mailto:lars.kjeldgaard@eb.dk). | |