File size: 960 Bytes
586f9cf 5dced34 586f9cf 5dced34 586f9cf 3f2f2b1 eafecbb 586f9cf eafecbb 586f9cf | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 | from transformers import pipeline
from huggingface_hub import login
import logging
import os
logger = logging.getLogger(__name__)
# Using a robust Sinhala sentiment analysis model from Hugging Face
MODEL_NAME = "sinhala-nlp/sinhala-sentiment-analysis-sinbert-small"
sentiment_pipeline = None
def load_model():
global sentiment_pipeline
if sentiment_pipeline is None:
try:
logger.info(f"Loading model {MODEL_NAME}...")
sentiment_pipeline = pipeline("sentiment-analysis", model=MODEL_NAME)
logger.info("Model loaded successfully.")
except Exception as e:
logger.error(f"Error loading model: {e}")
raise e
def predict_sentiment(text: str):
if not sentiment_pipeline:
raise RuntimeError("Model pipeline is not initialized.")
result = sentiment_pipeline(text)[0]
return {
"label": result["label"],
"score": float(result["score"])
}
|