readme: ---
  language: 
  - en
  - de
  license: apache-2.0
  datasets:
  - wmt14
  tags:
  - translation
  ---
  
  # bert2bert_L-24_wmt_de_en EncoderDecoder model
  
  The model was introduced in 
  [this paper](https://arxiv.org/abs/1907.12461) by Sascha Rothe, Shashi Narayan, Aliaksei Severyn and first released in [this repository](https://tfhub.dev/google/bertseq2seq/bert24_de_en/1). 
  
  The model is an encoder-decoder model that was initialized on the `bert-large` checkpoints for both the encoder 
  and decoder and fine-tuned on German to English translation on the WMT dataset, which is linked above.
  
  Disclaimer: The model card has been written by the Hugging Face team.
  
  ## How to use
  
  You can use this model for translation, *e.g.*
  
  ```python
  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
  
  tokenizer = AutoTokenizer.from_pretrained("google/bert2bert_L-24_wmt_de_en", pad_token="<pad>", eos_token="</s>", bos_token="<s>")
  model = AutoModelForSeq2SeqLM.from_pretrained("google/bert2bert_L-24_wmt_de_en")
  
  sentence = "Willst du einen Kaffee trinken gehen mit mir?"
  
  input_ids = tokenizer(sentence, return_tensors="pt", add_special_tokens=False).input_ids
  output_ids = model.generate(input_ids)[0]
  print(tokenizer.decode(output_ids, skip_special_tokens=True))
  # should output
  # Want to drink a kaffee go with me? .
  ```
  