Update app.py

app.py

@@ -13,12 +13,12 @@ untrained_model.to(device)
 def generate(commentary_text, max_length, temperature):
     # Generate text using the finetuned model
     input_ids = trained_tokenizer(commentary_text, return_tensors="pt").input_ids.to(device)
-    trained_output = trained_model.generate(input_ids, max_length=max_length, num_beams=5, do_sample=False, temperature=temperature)
+    trained_output = trained_model.generate(input_ids, max_length=max_length, num_beams=5, do_sample=True, temperature=temperature)
     trained_text = trained_tokenizer.decode(trained_output[0], skip_special_tokens=True)
     
     # Generate text using the base model
     input_ids = untrained_tokenizer(commentary_text, return_tensors="pt").input_ids.to(device)
-    untrained_output = untrained_model.generate(input_ids, max_length=max_length, num_beams=5, do_sample=False,temperature=temperature)
+    untrained_output = untrained_model.generate(input_ids, max_length=max_length, num_beams=5, do_sample=True,temperature=temperature)
     untrained_text = untrained_tokenizer.decode(untrained_output[0], skip_special_tokens=True)
     
     return trained_text, untrained_text
@@ -27,13 +27,13 @@ def generate(commentary_text, max_length, temperature):
 iface = gr.Interface(
     fn=generate, 
     inputs=[
-        gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here...", label="Prompt"),
-        gr.inputs.Slider(minimum=10, maximum=100, default=50, label="Max Length"),        
-        gr.inputs.Slider(minimum=0.1, maximum=1.0, default=0.7, label="Temperature")
+        gr.Textbox(lines=2, placeholder="Enter your prompt here...", label="Prompt"),
+        gr.Slider(minimum=10, maximum=100, default=50, label="Max Length"),        
+        gr.Slider(minimum=0.1, maximum=1.0, default=0.7, label="Temperature")
     ], 
     outputs=[
-        gr.outputs.Textbox(label="commentary generation from finetuned GPT2 Model"), 
-        gr.outputs.Textbox(label="commentary generation from base GPT2 Model")
+        gr.Textbox(label="commentary generation from finetuned GPT2 Model"), 
+        gr.Textbox(label="commentary generation from base GPT2 Model")
     ],
     title="GPT-2 Text Generation",
     description="start writing a cricket commentary and GPT-2 will continue it using both a finetuned and base model."