
Transformer with a Pointer Generator mechanism to facilitate copying of words from the input.
Sequence length padded to a multiple of 8 to better use tensor cores and reduce training time.

5. Now let's take a look at how to generate a summary with our new medical report generation system:
```python
import torch
from examples.pointer_generator.pointer_generator_src.transformer_pg import TransformerPointerGeneratorModel
Patient-Doctor conversation
input = "[doctor] Lisa Simpson, thirty six year old female, presents to the clinic today because " \
        "she has severe right wrist pain"
Load the model
model = TransformerPointerGeneratorModel.from_pretrained(data_name_or_path=,
                                                         model_name_or_path=,
                                                         checkpoint_file="checkpoint_best.pt")
result = model.translate([input], beam=2)
print(result[0])