Edit model card

-- EMODa --

BERT-model for danish multi-class classification of emotions

Classifies a danish sentence into one of 6 different emotions:

Danish emotion Ekman's emotion
😞 Afsky Disgust
😨 Frygt Fear
😄 Glæde Joy
😱 Overraskelse Surprise
😢 Tristhed Sadness
😠 Vrede Anger

How to use

from transformers import pipeline

model_path = "NikolajMunch/danish-emotion-classification"
classifier = pipeline("sentiment-analysis", model=model_path, tokenizer=model_path)
prediction = classifier("Jeg er godt nok ked af at mine SMS'er er slettet")

print(prediction)
# [{'label': 'Tristhed', 'score': 0.9725030660629272}]

or

from transformers import AutoTokenizer, AutoModelForSequenceClassification
  
tokenizer = AutoTokenizer.from_pretrained("NikolajMunch/danish-emotion-classification")

model = AutoModelForSequenceClassification.from_pretrained("NikolajMunch/danish-emotion-classification")
Downloads last month
62
Hosted inference API
Text Classification
Examples
Examples
This model can be loaded on the Inference API on-demand.