LX)

import torch

from pytorch_transformers import RobertaTokenizer, RobertaForSequenceClassification
# RoBERTa tokenizer and model loaded from saved checkpoint

tokenizer = RobertaTokenizer.from_pretrained("roberta-base")

model = RobertaForSequenceClassification.from_pretrained("roberta-base")

# Sequence encoded with the correct special separation tokens

sequence_0 = "Is this Jacksonville?"

sequence_1 = "No it is not."

input_ids = torch.tensor([tokenizer.encode(sequence_0, sequence_l, add_special_tokens=True)])
# Returns the loss and the associated logits

output = model(input_ids)