readme: ---
  language: de
  widget:
  - text: My name is Karl and I live in Aachen.
  tags:
  - translation 
  datasets:
  - wmt19
  license: gpl
  ---
  
  <h2> English to German Translation </h2>
  
  
  Model Name: Tanhim/translation-En2De <br />
  language: German or Deutsch  <br />
  thumbnail: https://huggingface.co/Tanhim/translation-En2De <br />
  
  ### How to use
  You can use this model directly with a pipeline for machine translation. Since the generation relies on some randomness, I
  set a seed for reproducibility:
  ```python
  >>> from transformers import pipeline, set_seed
  >>> text_En2De= pipeline('translation', model='Tanhim/translation-En2De', tokenizer='Tanhim/translation-En2De')
  >>> set_seed(42)
  >>> text_En2De("My name is Karl and I live in Aachen")
  
  ```
  ### beta version