model.py

# model.py
import torch
from transformers import DistilBertTokenizer, DistilBertForSequenceClassification

tokenizer = DistilBertTokenizer.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english")
model = DistilBertForSequenceClassification.from_pretrained("distilbert-base-uncased-finetuned-sst-2-english")

def get_sentiment(text):
    inputs = tokenizer(text, return_tensors="pt")
    with torch.no_grad():
        logits = model(**inputs).logits
    predicted_class_id = logits.argmax().item()
    return model.config.id2label[predicted_class_id]

if __name__ == '__main__':
    test_text = "This movie was NOt great!"
    sentiment = get_sentiment(test_text)
    print(f"Sentiment: {sentiment}")