Update app.py

app.py

@@ -8,19 +8,19 @@ import torch
 
 #Summarization Fine Tune Model
 
-model_path = "leadingbridge/summarization"
-tokenizer = AutoTokenizer.from_pretrained(model_path)
-model = T5ForConditionalGeneration.from_pretrained(model_path)
+def summarize_text(text, model_path="leadingbridge/summarization"):
+    # Load the tokenizer and model
+    tokenizer = AutoTokenizer.from_pretrained(model_path)
+    model = T5ForConditionalGeneration.from_pretrained(model_path)
 
-def summarize_text(text):
-	text = "This is the initial testing text"
     # Tokenize the input text
-	inputs = tokenizer.encode(text, return_tensors="pt")
-	# Generate the summary
-	summary_ids = model.generate(inputs)
-	summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
-	# Return the summary
-	return summary
+    inputs = tokenizer.encode(text, return_tensors="pt")
+
+    # Generate the summary
+    summary_ids = model.generate(inputs)
+    summary = tokenizer.decode(summary_ids[0], skip_special_tokens=True)
+
+    return summary
 
 # Sentiment Analysis Pre-Trained Model
 model_path = "leadingbridge/sentiment-analysis"