readme: ---
  language: en
  license: apache-2.0
  ---
  
  # Roberta2Roberta_L-24_wikisplit 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/roberta24_cnndm/1). 
  
  The model is an encoder-decoder model that was initialized on the `roberta-large` checkpoints for both the encoder 
  and decoder and fine-tuned on sentence splitting on the [WikiSplit](https://github.com/google-research-datasets/wiki-split) dataset.
  
  Disclaimer: The model card has been written by the Hugging Face team.
  
  ## How to use
  
  You can use this model for sentence splitting, *e.g.*
  
  **IMPORTANT**: The model was not trained on the `"` (double quotation mark) character -> so the before tokenizing the text, 
  it is advised to replace all `"` (double quotation marks) with two single `'` (single quotation mark).
  
  ```python
  from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
  
  tokenizer = AutoTokenizer.from_pretrained("google/roberta2roberta_L-24_wikisplit")
  model = AutoModelForSeq2SeqLM.from_pretrained("google/roberta2roberta_L-24_wikisplit")
  
  long_sentence = """Due to the hurricane, Lobsterfest has been canceled, making Bob very happy about it and he decides to open Bob 's Burgers for customers who were planning on going to Lobsterfest."""
  
  input_ids = tokenizer(tokenizer.bos_token + long_sentence + tokenizer.eos_token, return_tensors="pt").input_ids
  output_ids = model.generate(input_ids)[0]
  print(tokenizer.decode(output_ids, skip_special_tokens=True))
  # should output
  # Due to the hurricane, Lobsterfest has been canceled, making Bob very happy about it. He decides to open Bob's Burgers for customers who were planning on going to Lobsterfest. 
  ```
  