This is a model checkpoint for "[Structured Pruning Learns Compact and Accurate Models](https://arxiv.org/pdf/2204.00408.pdf)". The model is pruned from `bert-base-uncased` to a 95% sparsity on dataset QNLI. Please go to [our repository](https://github.com/princeton-nlp/CoFiPruning) for more details on how to use the model for inference. Note that you would have to use the model class specified in our repository to load the model.

{}
transformers pytorch bert text-classification arxiv:2204.00408 autotrain_compatible endpoints_compatible region:us
TAGS
#transformers #pytorch #bert #text-classification #arxiv-2204.00408 #autotrain_compatible #endpoints_compatible #region-us 

This is a model checkpoint for "Structured Pruning Learns Compact and Accurate Models". The model is pruned from 'bert-base-uncased' to a 95% sparsity on dataset QNLI. Please go to our repository for more details on how to use the model for inference. Note that you would have to use the model class specified in our repository to load the model.

TAGS
#transformers #pytorch #bert #text-classification #arxiv-2204.00408 #autotrain_compatible #endpoints_compatible #region-us 

passage: TAGS
#transformers #pytorch #bert #text-classification #arxiv-2204.00408 #autotrain_compatible #endpoints_compatible #region-us 
