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README.md
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---
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language: en
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tags:
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- bart
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- question
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- generation
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- seq2seq
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datasets:
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- unifiedQA
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metrics:
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- bleu
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- rouge
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pipeline_tag: text2text-generation
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widget:
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- 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 ."
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---
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# bart-distractor-generation-both
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## Model description
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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.
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It is based on a pretrained `bart-base` model.
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#### How to use
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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:
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```
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answer \n context
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```
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The input sequence can then be encoded and passed as the `input_ids` argument in the model's `generate()` method.
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