DeeBERT
DeeBERT
**DeeBERT** is a method for accelerating [BERT](https://paperswithcode.com/method/bert) inference. It inserts extra classification layers (which are referred to as off-ramps) between each [transformer](https://paperswithcode.com/method/transformer) layer of BERT. All transformer layers and off-ramps are jointly fine-tuned on a given downstream dataset. At inference time, after a sample goes through a transformer layer, it is passed to the following off-ramp. If the off-ramp is confident of the prediction, the result is returned; otherwise, the sample is sent to the next transformer layer.
DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference
https://paperswithcode.com/paper/deebert-dynamic-early-exiting-for
DeeBERT: Dynamic Early Exiting for Accelerating BERT Inference