Language Detection

docker pull cargoshipsh/language-detection

Automatically detect the language of an input text. This model is based on FastText and is trained on data from Wikipedia, Tatoeba and SETimes. The model itself is only 917kB in size and doesn't require a GPU to run.



Predicted Language



The model itself is licensed under Creative Commons Attribution-Share-Alike License 3.0. The code for the API wrapper is licensed under MIT License.

System Requirements

Minimum: 1GB RAM, 1 vCPU
Recommended: 2GB RAM, 2 vCPU


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 Started


Input [POST]

  "text": "This is a text in English"


  "language": "en"

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.


Make sure you have Docker installed then run the following command:

docker run -p 80:80 --env API_KEY=CHANGE_ME cargoshipsh/language-detection

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":"Hello, World!"}' http://localhost:80

You see the output of the model in the terminal.


Need help?

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