tokenizer = AutoTokenizer.from_pretrained("google/roberta2roberta_L-24_discofuse")
input_ids = tokenizer(
...     "This is the first sentence. This is the second sentence.", add_special_tokens=False, return_tensors="pt"
).input_ids
outputs = sentence_fuser.generate(input_ids)
print(tokenizer.decode(outputs[0]))
```
Tips:
[BertGenerationEncoder] and [BertGenerationDecoder] should be used in
  combination with [EncoderDecoder].
For summarization, sentence splitting, sentence fusion and translation, no special tokens are required for the input.
  Therefore, no EOS token should be added to the end of the input.
This model was contributed by patrickvonplaten. The original code can be
found here.
BertGenerationConfig
[[autodoc]] BertGenerationConfig
BertGenerationTokenizer
[[autodoc]] BertGenerationTokenizer
