readme: ---
  license: apache-2.0
  datasets:
  - tals/vitaminc
  - SetFit/mnli
  - snli
  - fever
  - paws
  - scitail
  language:
  - en
  ---
  This is an NLI model based on T5-XXL that predicts a binary label ('1' - Entailment, '0' - No entailment).
  
  It is trained similarly to the NLI model described in the [TRUE paper (Honovich et al, 2022)](https://arxiv.org/pdf/2204.04991.pdf), but using the following datasets instead of ANLI:
  - SNLI ([Bowman et al., 2015](https://arxiv.org/abs/1508.05326))
  - MNLI ([Williams et al., 2018](https://aclanthology.org/N18-1101.pdf))
  - Fever ([Thorne et al., 2018](https://aclanthology.org/N18-1074.pdf))
  - Scitail ([Khot et al., 2018](http://ai2-website.s3.amazonaws.com/publications/scitail-aaai-2018_cameraready.pdf))
  - PAWS ([Zhang et al. 2019](https://arxiv.org/abs/1904.01130))
  - VitaminC ([Schuster et al., 2021](https://arxiv.org/pdf/2103.08541.pdf))
  
  The input format for the model is: "premise: PREMISE_TEXT hypothesis: HYPOTHESIS_TEXT".
  