haipradana/indobert-indonesia-satire-sarcastic-classification-model

import torch
from transformers import AutoTokenizer, AutoModelForSequenceClassification

# Load model
tokenizer = AutoTokenizer.from_pretrained("indobert-indonesia-sarcastic-satire-classification/model")
model = AutoModelForSequenceClassification.from_pretrained("indobert-indonesia-sarcastic-satire-classification/model")

# Predict
def predict(text: str):
    inputs = tokenizer(text, return_tensors='pt', truncation=True, padding=True, max_length=512)
    with torch.no_grad():
        outputs = model(**inputs)
    logits = outputs.logits
    prediction = torch.argmax(logits, dim=1).item()
    return 'sarcasm' if prediction == 1 else 'not sarcasm'

# Example
result = predict("Kamu penulis ya? pandai sekali mengarang cerita")
print(result) #output = sarcasm

cd scripts
python predict.py