How should I try to feed new memory states to the next segments
Here is a simple exemple for my training loop based on Trainer class
```python
transfo_xl_config = transformers.TransfoXLConfig(**hparams)
model = transformers.TransfoXLForSequenceClassification(transfo_xl_config)

training_args = transformers.TrainingArguments("test_trainer", no_cuda=True)
trainer = transformers.Trainer(
    model=model,
    args=training_args,
    train_dataset=MyDataset('train'),
    eval_dataset=MyDataset('test')
)
trainer.train()
```
The question is how should I feed new memory states to the next segments in the next batch when using TransfoXLModel
cc @sgugger <|||||>The `Trainer` does not support the transformer XL model, so you should run a manual training loop that you can power by [Accelerate](https://github.com/huggingface/accelerate) if you need distributed training.<|||||>> The `Trainer` does not support the transformer XL model, so you should run a manual training loop that you can power by [Accelerate](https://github.com/huggingface/accelerate) if you need distributed training.

Thanks