How can i add a Bi-LSTM layer on top of some model?like xlm_roberta
I'm using pytorch and I'm using the base pretrained bert to classify sentences for hate speech. I want to implement a Bi-LSTM layer that takes as an input all outputs of the latest transformer encoder from the bert model as a new model (class that implements nn.Module), and i got confused with the nn.LSTM parameters. 
Hi,

Please ask training-related questions on our [forum](https://discuss.huggingface.co/) instead of here, as we'd like to keep Github issues for bugs/feature requests.

Thanks!