Update app.py

app.py

@@ -8,7 +8,7 @@ import pandas as pd
 
 # Load paraphrase model and tokenizer
 model = T5ForConditionalGeneration.from_pretrained('ramsrigouthamg/t5_paraphraser')
-tokenizer = T5Tokenizer.from_pretrained('t5-base')
+tokenizer = T5Tokenizer.from_pretrained('t5-base', legacy=False)  # Explicitly set legacy=False
 
 device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
 model = model.to(device)
@@ -232,7 +232,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css, js=custom_js) as demo:
         outputs=output_text
     )
     
-    # Calculate and display metrics on load
+    # Calculate and display metrics on load without _js
     test_sentences = [
         "The quick brown fox jumps over the lazy dog.",
         "Artificial intelligence is transforming industries.",
@@ -240,12 +240,7 @@ with gr.Blocks(theme=gr.themes.Soft(), css=custom_css, js=custom_js) as demo:
         "He enjoys reading books on machine learning.",
         "The stock market fluctuates daily due to various factors."
     ]
-    demo.load(
-        fn=calculate_precision_recall_accuracy,
-        inputs=None,
-        outputs=metrics_output,
-        _js="() => { return ['" + "', '".join(test_sentences) + "']; }"
-    )
+    metrics_output.value = calculate_precision_recall_accuracy(test_sentences)
 
 # Launch Gradio app
 demo.launch(share=False)