Model name 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 t5 base model. Intended uses & limitations 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. How to use 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 input ids argument in the model's generate() method. For best results, a large number of questions can be generated, and then filtered using iarfmoose/bert base cased qa evaluator. For examples, please see https://github.com/iarfmoose/question generator. Limitations and bias The model is limited to generating questions in the same style as those found in SQuAD, CoQA, and MSMARCO. The generated questions can potentially be leading or r…
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