Training transformer XL from scratch with my own dataset
## ❓ Questions & Help
Is it possible to train a transformer XL model from scratch with my own dataset? 
Just initialize the model with default params and compile & fit the model?
<!-- A clear and concise description of the question. -->

I think yes, 
Just load the model (class) and then start training. As it is mentioned [here](https://huggingface.co/transformers/model_doc/transformerxl.html#transformers.TransfoXLModel), model classes are just a PyTorch torch.nn.Module sub-class.

> This model is a PyTorch torch.nn.Module sub-class. Use it as a regular PyTorch Module and refer to the PyTorch documentation for all matter related to general usage and behavior.<|||||>Is it also possible to train tensorflow model?<|||||>If we think about [this](https://huggingface.co/transformers/model_doc/transformerxl.html#tftransfoxlmodel) expression, yes. 

> This model is a tf.keras.Model tf.keras.Model sub-class. Use it as a regular TF 2.0 Keras Model and refer to the TF 2.0 documentation for all matter related to general usage and behavior.

Also, check [this](https://github.com/huggingface/transformers#quick-tour-tf-20-training-and-pytorch-interoperability) out.<|||||>Thanks very much!