metadata

language:
  - de
tags:
  - deepset/gbert-large

German Sentiment Analysis

This model predicts sentiment for German text.

Usage

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}]

Credits / Special Thanks:

This model was fine-tuned by Aaron Chibb. It is trained on twitter dataset by tygiangz and based on gBERT-large by deepset.