A model fine-tuned for sentiment analysis based on vinai/phobert-base.
Labels:
- NEG: Negative
- POS: Positive
- NEU: Neutral
Dataset: Comments on Shoppe (https://shopee.vn/)
Usage
from transformers import AutoTokenizer, AutoModelForSequenceClassification import torch
tokenizer = AutoTokenizer.from_pretrained("lamsytan/sentiment-analysis-base-phobert") model = AutoModelForSequenceClassification.from_pretrained("lamsytan/sentiment-analysis-base-phobert")
sentence = "Áo đẹp lắm nhá lần sau sẽ ghé tiếp ạ"
inputs = tokenizer(sentence, return_tensors="pt", padding=True, truncation=True)
with torch.no_grad(): outputs = model(**inputs) logits = outputs.logits probabilities = torch.softmax(logits, dim=-1)
print(probabilities.tolist()) # Output: # [[0.010827462188899517, 0.9538241624832153, 0.035348404198884964]] # ^ ^ ^ # NEG POS NEU