Sentiment Analysis [German]
docker pull cargoshipsh/sentiment-de
Automatically detect the language of an input text. The model was provided by Oliver Guhr and uses Googles Bert architecture. It was trained on 1.8 million German-language samples. The training data contains texts from various domains like Twitter, Facebook and movie, app and hotel reviews. The model itself is 440MB and needs an aditional 500kB for the tokenizer.
Demo
Input
Predicted Sentiment
positive
License
The model is licensed under MIT License. The code for the API wrapper is also licensed under MIT License.
System Requirements
Minimum: 1GB RAM, 1 vCPU
Recommended: 2GB RAM, 2 vCPU
API
If you don't want to implement the model all by yourself, no worries. Benefit from our easy to use API and get started right away!
Get StartedUsage
Input [POST]
{
"text": "Ich mag Dich."
}
Output
{
"sentiment": "positive"
}
You need to set an API Key via the environment variable API_KEY to run the image and set the X-API-KEY header in your request with the same KEY.
Need a more detailed setup guide?
To get more detailed instructions how to get started please check out our quick start guide in the docs.
Example
Make sure you have Docker installed then run the following command:
docker run -p 80:80 --env API_KEY=CHANGE_ME cargoshipsh/sentiment-de:main
In a new terminal window, run the following command to call the API
curl -X POST -H 'Content-type: application/json' -H 'X-API-Key: CHANGE_ME' --data '{"text":"Ich mag Dich!"}' http://localhost:80
You see the output of the model in the terminal.
{"sentiment":"positive"}