Update to use fine-tuned T5 model and fix Gradio launch parameters

app.py

@@ -1,9 +1,10 @@
 import gradio as gr
 from transformers import T5Tokenizer, T5ForConditionalGeneration
 
-# Load the base T5 model and tokenizer
-model = T5ForConditionalGeneration.from_pretrained('t5-small')
-tokenizer = T5Tokenizer.from_pretrained('t5-small')
+# Load the fine-tuned T5 model and tokenizer
+model_path = "C:/Users/admin/Desktop/my_fine_tuned_t5_small"
+model = T5ForConditionalGeneration.from_pretrained(model_path)
+tokenizer = T5Tokenizer.from_pretrained(model_path)
 
 def generate_clinical_report(input_text):
     """
@@ -59,7 +60,7 @@ if __name__ == "__main__":
         show_api=True,
         allowed_paths=None,  # Allow all paths
         quiet=True,  # Reduce logging noise
-        enable_queue=True,
         api_open=True,  # Explicitly enable API access
-        cors_allowed_origins="*"  # Allow cross-origin requests
+        cors_allowed_origins="*",  # Allow cross-origin requests
+        concurrency_count=1  # Enable queuing with concurrency
     )