tokenizer = AutoTokenizer.from_pretrained("vinai/phobert-base")
INPUT TEXT MUST BE ALREADY WORD-SEGMENTED!
line = "Tôi là sinh_viên trường đại_học Công_nghệ ."
input_ids = torch.tensor([tokenizer.encode(line)])
with torch.no_grad():
...     features = phobert(input_ids)  # Models outputs are now tuples
With TensorFlow 2.0+:
from transformers import TFAutoModel
phobert = TFAutoModel.from_pretrained("vinai/phobert-base")
```
This model was contributed by dqnguyen. The original code can be found here.
PhobertTokenizer
[[autodoc]] PhobertTokenizer
