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@@ -20,7 +20,7 @@ The BERT Emotion model classifies a Danish text in one of the following class:
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  It is based on the pretrained [Danish BERT](https://github.com/certainlyio/nordic_bert) model by BotXO which has been fine-tuned on social media data.
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- This model should be used after detecting whether the text contains emotion or not, using the binary [BERT Emotion model](https://huggingface.co/DaNLP/da-bert-emotion-binary).
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  See the [DaNLP documentation](https://danlp-alexandra.readthedocs.io/en/latest/docs/tasks/sentiment_analysis.html#bert-emotion) for more details.
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@@ -29,8 +29,8 @@ Here is how to use the model:
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  ```python
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  from transformers import BertTokenizer, BertForSequenceClassification
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- model = BertForSequenceClassification.from_pretrained("DaNLP/da-bert-emotion-classification")
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- tokenizer = BertTokenizer.from_pretrained("DaNLP/da-bert-emotion-classification")
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  ```
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  ## Training data
 
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  It is based on the pretrained [Danish BERT](https://github.com/certainlyio/nordic_bert) model by BotXO which has been fine-tuned on social media data.
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+ This model should be used after detecting whether the text contains emotion or not, using the binary [BERT Emotion model](https://huggingface.co/alexandrainst/da-bert-emotion-binary).
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  See the [DaNLP documentation](https://danlp-alexandra.readthedocs.io/en/latest/docs/tasks/sentiment_analysis.html#bert-emotion) for more details.
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  ```python
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  from transformers import BertTokenizer, BertForSequenceClassification
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+ model = BertForSequenceClassification.from_pretrained("alexandrainst/da-bert-emotion-classification")
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+ tokenizer = BertTokenizer.from_pretrained("alexandrainst/da-bert-emotion-classification")
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  ```
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  ## Training data