add support to MPNetForCausalLM
Author: jwengr
Pull request: yes

# What does this PR do?

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Fixes [#21379](https://github.com/huggingface/transformers/issues/21379#issue-1563845759)

Goal: Add support to MPNetForCausalLM
Changes:

Modified [modeling_mpnet.py](https://github.com/huggingface/transformers/blob/master/src/transformers/models/mpnet/modeling_mpnet.py):  add cross-attention and accept arguments encoder_hidden_states & encoder_attention_mask ; and added the new class MPNetForCausalLM;

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Comments:
_The documentation is not available anymore as the PR was closed or merged._

Hi there! MPNet is an encoder model, so there are no checkpoints available that will work for causal LM objective. Why are you interested in adding this model?

Hi @sgugger!
I've recently been using sentense-transformers library which relies on transformers for sentence embedding.
and certain features(https://www.sbert.net/docs/package_reference/losses.html#denoisingautoencoderloss) require decoder part of model.
mpnet show good performance in sentence-transformers library and i tried to write a decoder part to further improve this.
there was a similar issue before [#14737](https://github.com/huggingface/transformers/issues/14737)

There is no `DistilBertForCausalLM` either in the library, so the issue you link to doesn't really have a link. Like I said, there are no pretrained checkpoints for MPNet and causal language modeling, so even if we add this architecture, you won't be able to use it in sentence-transformers since you will get garbage outputs.