File size: 2,120 Bytes
b31728c ea54a5a b31728c ea54a5a b31728c e6f08d5 b31728c ea54a5a b31728c | 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 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 | import os
import sys
import torch
import numpy as np
from transformers import AutoTokenizer ,AutoModelForSequenceClassification
sys .stdout .reconfigure (encoding ='utf-8')
def main ():
print ("="*60 )
print (" Loading Urdu Sentiment & Emotion Models...")
print ("="*60 )
base_dir =os .path .dirname (os .path .abspath (__file__ ))
sentiment_dir =os .path .join (base_dir ,"models","sentiment_model")
emotion_dir =os .path .join (base_dir ,"models","emotion_model")
sentiment_map ={0 :"Negative 😠",1 :"Neutral 😐",2 :"Positive 😊"}
emotion_map ={0 :"Joy 😄",1 :"Anger 😡",2 :"Fear 😨",3 :"Sadness 😢"}
try :
print ("Loading Tokenizer...")
tokenizer =AutoTokenizer .from_pretrained (sentiment_dir )
print ("Loading Sentiment Model...")
sentiment_model =AutoModelForSequenceClassification .from_pretrained (sentiment_dir )
print ("Loading Emotion Model...")
emotion_model =AutoModelForSequenceClassification .from_pretrained (emotion_dir )
except Exception as e :
print (f"Error loading models. Are you sure they finished training? ({e })")
return
print ("\nModels loaded successfully!")
print ("Type an Urdu sentence (Roman or Script) to test them. Type 'exit' to quit.\n")
while True :
text =input ("Enter Urdu text: ")
if text .strip ().lower ()in ['exit','quit','q']:
break
if not text .strip ():
continue
inputs =tokenizer (text ,return_tensors ="pt",truncation =True ,max_length =128 )
with torch .no_grad ():
sentiment_out =sentiment_model (**inputs ).logits
emotion_out =emotion_model (**inputs ).logits
sentiment_idx =np .argmax (sentiment_out .numpy (),axis =-1 )[0 ]
emotion_idx =np .argmax (emotion_out .numpy (),axis =-1 )[0 ]
print ("-"*40 )
print (f"Sentiment : {sentiment_map [sentiment_idx ]}")
print (f"Emotion : {emotion_map [emotion_idx ]}")
print ("-"*40 +"\n")
if __name__ =="__main__":
main ()
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