How to use from the
Use from the
Transformers library
# Use a pipeline as a high-level helper
from transformers import pipeline

pipe = pipeline("text-classification", model="alexandrainst/da-subjectivivity-classification-base")
# Load model directly
from transformers import AutoTokenizer, AutoModelForSequenceClassification

tokenizer = AutoTokenizer.from_pretrained("alexandrainst/da-subjectivivity-classification-base")
model = AutoModelForSequenceClassification.from_pretrained("alexandrainst/da-subjectivivity-classification-base")
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Danish BERT Tone for the detection of subjectivity/objectivity

The BERT Tone model detects whether a text (in Danish) is subjective or objective. The model is based on the finetuning of the pretrained Danish BERT model by BotXO.

See the DaNLP documentation for more details.

Here is how to use the model:

from transformers import BertTokenizer, BertForSequenceClassification

model = BertForSequenceClassification.from_pretrained("alexandrainst/da-subjectivivity-classification-base")
tokenizer = BertTokenizer.from_pretrained("alexandrainst/da-subjectivivity-classification-base")

Training data

The data used for training come from the Twitter Sentiment and EuroParl sentiment 2 datasets.

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Dataset used to train alexandrainst/da-subjectivivity-classification-base