

TITLE
Edgeformer

COMMENTS
7

REACTIONS
+1: 0
-1: 0
laugh: 0
hooray: 0
heart: 3
rocket: 0
eyes: 0

BODY
# 🌟 New model addition

## Model description

[EdgeFormer: A Parameter-Efficient Transformer for On-Device Seq2seq Generation](https://arxiv.org/abs/2202.07959)

EdgeFormer: A Parameter-Efficient Transformer for On-Device Seq2seq Generation. Tao Ge and Furu Wei

March 2022: release code and pretrained checkpoints.

## Open source status

* [x] the model implementation is available: https://github.com/microsoft/unilm/blob/900f5416c8137a753b1c8f53cd5015d0ceca7061/edgelm/fairseq/models/transformer/transformer_legacy.py#L226
* [x] the model weights are available: https://github.com/microsoft/unilm/tree/900f5416c8137a753b1c8f53cd5015d0ceca7061/edgelm#pretrained-models
* [x] who are the authors: Maybe @gitnlp 

Happy to help with a model contribution here!