Update main.py

main.py

@@ -39,7 +39,7 @@ sentiment_model.eval()
 
 def analyze_text(text):
     # Tokenize input text for NER
-    ner_inputs = ner_tokenizer(text, max_length= 1024, truncation= True, padding= "max_length", return_tensors="pt")
+    ner_inputs = ner_tokenizer(text, max_length= 514, truncation= True, padding= "max_length", return_tensors="pt")
 
     input_ids = ner_inputs['input_ids']
 
@@ -59,7 +59,7 @@ def analyze_text(text):
     ner_labels = [f"{token}: {label}" for token, label in zip(tokens, ner_labels)]
 
     # Tokenize input text for sentiment analysis
-    sentiment_inputs = sentiment_tokenizer(text, max_length= 1024, truncation= True, padding= "max_length", return_tensors="pt")
+    sentiment_inputs = sentiment_tokenizer(text, max_length= 514, truncation= True, padding= "max_length", return_tensors="pt")
 
     # Perform sentiment analysis
     with torch.no_grad():