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The following model is a Pytorch pre-trained model obtained from converting Tensorflow checkpoint found in the [official Google BERT repository](https://github.com/google-research/bert). These BERT variants were introduced in the paper [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962). These models are supposed to be trained on a downstream task.
If you use the model, please consider citing the paper
```
@misc{bhargava2021generalization,
title={Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics},
author={Prajjwal Bhargava and Aleksandr Drozd and Anna Rogers},
year={2021},
eprint={2110.01518},
archivePrefix={arXiv},
primaryClass={cs.CL}
}
```
Original Implementation and more info can be found in [this Github repository](https://github.com/prajjwal1/generalize_lm_nli).
You can check out:
- `prajjwal1/bert-tiny` (L=2, H=128)
- `prajjwal1/bert-mini` (L=4, H=256)
- `prajjwal1/bert-small` (L=4, H=512)
- `prajjwal1/bert-medium` (L=8, H=512)
[@prajjwal_1](https://twitter.com/prajjwal_1)
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