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 t5-base model. The model is trained to generate reading comprehension-style questions with answers extracted from a text. The model performs best with full sentence answers, but can also be used with single word or short phrase answers. The model takes concatenated answers and context as an input sequence, and will generate a full question sentence as an output sequence. The max sequence length is 512 tokens. Inputs should be organised into the following format: The input sequence can then be encoded and passed as the…
Independent publisher
Adam Montgomerie
iarfmoose
I'm a ML Engineer at Avanssion. I'm interested in applying NLP to language learning.
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Models on Hugging Face10
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