  the model as follows:
```python
  from transformers import T5Tokenizer, T5ForConditionalGeneration
tokenizer = T5Tokenizer.from_pretrained("t5-small")
  model = T5ForConditionalGeneration.from_pretrained("t5-small")
input_ids = tokenizer("translate English to German: The house is wonderful.", return_tensors="pt").input_ids
  labels = tokenizer("Das Haus ist wunderbar.", return_tensors="pt").input_ids
  # the forward function automatically creates the correct decoder_input_ids
  loss = model(input_ids=input_ids, labels=labels).loss
  ```
As you can see, only 2 inputs are required for the model in order to compute a loss: input_ids (which are the
  input_ids of the encoded input sequence) and labels (which are the input_ids of the encoded
  target sequence). The model will automatically create the decoder_input_ids based on the labels, by
