Exclusively German Encoders
Collection
German Encoder models for RAG / Classification tasks with German Tokenizer
•
3 items
•
Updated
•
3
This model predicts sentiment for German text.
First set up the model:
# if necessary:
# !pip install transformers
from transformers import pipeline
sentiment_model = pipeline(model="aari1995/German_Sentiment")
to use it:
sentence = ["Ich liebe die Bahn. Pünktlich wie immer ... -.-","Krasser Service"]
result = sentiment_model(sentence)
print(result)
#Output:
#[{'label': 'negative', 'score': 0.4935680031776428},{'label': 'positive', 'score': 0.5790663957595825}]
This model was fine-tuned by Aaron Chibb. It is trained on twitter dataset by tygiangz and based on gBERT-large by deepset.