Downloads · 30 days
75
0% of all-time downloads
aari1995/German_Sentiment
German_Sentiment is a text classification model from aari1995. Use it when you need a label for a piece of text. It is set up for transformers.
This model predicts sentiment for German text.
Downloads · 30 days
75
0% of all-time downloads
All-time downloads
87.3K
Public
Parameters
336M
2.7 GB on disk
Likes
5
Public
Click a slice to open those files.
.bin1.3 GB · 50%
How the weights are stored.
F32336M · 100%
From the Hugging Face model README
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.