readme: ---
  language: en
  tags:
  - bart
  - question
  - generation
  - seq2seq
  datasets:
  - unifiedQA
  metrics:
  - bleu
  - rouge
  pipeline_tag: text2text-generation
  widget:
  - text: "treehouses in france. \n When you ' re having a holiday , one of the main questions to ask is which hotel or apartment to choose . However , when it comes to France , you have another special choice : treehouses . In France , treehouses are offered to travelers as a new choice in many places . The price may be a little higher , but you do have a chance to _ your childhood memories . Alain Laurens , one of France ' s top treehouse designers , said , ' Most of the people might have the experience of building a den when they were young . And they like that feeling of freedom when they are children . ' Its fairy - tale style gives travelers a special feeling . It seems as if they are living as a forest king and enjoying the fresh air in the morning . Another kind of treehouse is the ' star cube ' . It gives travelers the chance of looking at the stars shining in the sky when they are going to sleep . Each ' star cube ' not only offers all the comfortable things that a hotel provides for travelers , but also gives them a chance to look for stars by using a telescope . The glass roof allows you to look at the stars from your bed ."
  ---
  # unifiedqg-bart-base
  
  ## Model description
  
  This model is a sequence-to-sequence question generator which takes an answer and context as an input, and generates a question as an output.   
  It is based on a pretrained `bart-base` model.     
  
  #### How to use
  
  The model takes concatenated context and answers as an input sequence, and will generate a full distractor sentence as an output sequence. The max sequence length is 1024 tokens. Inputs should be organised into the following format:   
  ```
  answer \n context 
  ```
  The input sequence can then be encoded and passed as the `input_ids` argument in the model's `generate()` method.
  
  