Danish BERT fine-tuned for Sentiment Analysis (Polarity)

This model detects polarity ('positive', 'neutral', 'negative') of danish texts.

It is trained and tested on Tweets annotated by Alexandra Institute.

Here is an example on how to load the model in PyTorch using the 🤗Transformers library:

from transformers import AutoTokenizer, AutoModelForSequenceClassification, pipeline
tokenizer = AutoTokenizer.from_pretrained("larskjeldgaard/senda")
model = AutoModelForSequenceClassification.from_pretrained("larskjeldgaard/senda")

# create 'senda' sentiment analysis pipeline 
senda_pipeline = pipeline('sentiment-analysis', model=model, tokenizer=tokenizer)

senda_pipeline("Sikke en dejlig dag det er i dag")
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Hosted inference API
Text Classification
Examples
Examples
This model can be loaded on the Inference API on-demand.