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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).
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- This is one of the smaller pre-trained BERT variants, together with [bert-mini](https://huggingface.co/prajjwal1/bert-mini), [bert-tiny](https://huggingface.co/prajjwal1/bert-tiny), [bert-small](https://huggingface.co/prajjwal1/bert-small) and [bert-medium](https://huggingface.co/prajjwal1/bert-medium). They were introduced in the study [Well-Read Students Learn Better: On the Importance of Pre-training Compact Models](https://arxiv.org/abs/1908.08962), and ported to HF for the study [Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics](https://arxiv.org/abs/2110.01518). These models are supposed to be trained on a downstream task.
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  If you use the model, please consider citing both the papers:
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  ```
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  }
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  ```
 
 
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  Other models to check out:
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  - `prajjwal1/bert-tiny` (L=2, H=128) [Model Link](https://huggingface.co/prajjwal1/bert-tiny)
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  - `prajjwal1/bert-mini` (L=4, H=256) [Model Link](https://huggingface.co/prajjwal1/bert-mini)
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- - `prajjwal1/bert-small` (L=4, H=512) [Model Link](https://huggingface.co/prajjwal1/bert-small)
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  - `prajjwal1/bert-medium` (L=8, H=512) [Model Link](https://huggingface.co/prajjwal1/bert-medium)
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  Original Implementation and more info can be found in [this Github repository](https://github.com/prajjwal1/generalize_lm_nli).
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  Twitter: [@prajjwal_1](https://twitter.com/prajjwal_1)
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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).
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+ This is one of the smaller pre-trained BERT variants, together with [bert-tiny](https://huggingface.co/prajjwal1/bert-small), [bert-mini]([bert-small](https://huggingface.co/prajjwal1/bert-mini) and [bert-medium](https://huggingface.co/prajjwal1/bert-medium). They were introduced in the study `Well-Read Students Learn Better: On the Importance of Pre-training Compact Models` ([arxiv](https://arxiv.org/abs/1908.08962)), and ported to HF for the study `Generalization in NLI: Ways (Not) To Go Beyond Simple Heuristics` ([arXiv](https://arxiv.org/abs/2110.01518)). These models are supposed to be trained on a downstream task.
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  If you use the model, please consider citing both the papers:
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  ```
 
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  }
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  ```
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+ Config of this model:
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+ - `prajjwal1/bert-small` (L=4, H=512) [Model Link](https://huggingface.co/prajjwal1/bert-small)
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  Other models to check out:
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  - `prajjwal1/bert-tiny` (L=2, H=128) [Model Link](https://huggingface.co/prajjwal1/bert-tiny)
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  - `prajjwal1/bert-mini` (L=4, H=256) [Model Link](https://huggingface.co/prajjwal1/bert-mini)
 
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  - `prajjwal1/bert-medium` (L=8, H=512) [Model Link](https://huggingface.co/prajjwal1/bert-medium)
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  Original Implementation and more info can be found in [this Github repository](https://github.com/prajjwal1/generalize_lm_nli).
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  Twitter: [@prajjwal_1](https://twitter.com/prajjwal_1)