sentiment classification

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Dataset: Từ từ sẽ được update

Usage

import torch
from transformers import RobertaForSequenceClassification, AutoTokenizer

model = RobertaForSequenceClassification.from_pretrained("hunterdie333/Dazk-Nhan-Dien-Tot-Xau")

tokenizer = AutoTokenizer.from_pretrained("hunterdie333/Dazk-Nhan-Dien-Tot-Xau", use_fast=False)

# Just like PhoBERT: INPUT TEXT MUST BE ALREADY WORD-SEGMENTED!
sentence = 'Mô hình được clone lại bởi DazkDev'  

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

with torch.no_grad():
    out = model(input_ids)
    print(out.logits.softmax(dim=-1).tolist())
    # Output:
    # [[0.293, 0.040, 0.667]]
    #     ^      ^      ^
    #    NEG    POS    NEU