import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification, RobertaForSequenceClassification
import numpy as np

tokenizer = AutoTokenizer.from_pretrained("quanqnv19/VN-Sentiment-Classification")
model = AutoModelForSequenceClassification.from_pretrained("quanqnv19/VN-Sentiment-Classification")

# sentence cần được segment bằng VnCoreNLP
sentence = "dùng tạm ổn"

input_ids = torch.tensor([tokenizer.encode(sentence)])

with torch.no_grad():
out = model(input_ids)
print(out.logits.softmax(dim=-1).tolist())
print(np.argmax(out[0], axis=1).flatten()[0].item())