Update app.py

app.py

@@ -128,31 +128,31 @@ with gr.Blocks(theme="abidlabs/Lime") as demo:
         gr.Markdown("Pre-trained TURNA. Enter text to start generating.")
         with gr.Column():
             with gr.Row():
-                max_new_tokens = gr.Slider(label = "Maximum length",
-                		minimum = 0,
-                		maximum = 512,
-                		value = 128)
-                length_penalty = gr.Slider(label = "Length penalty",
-                    		value=1.0)
-                top_k = gr.Slider(label = "Top-k", value=10)
-                top_p = gr.Slider(label = "Top-p", value=0.95)
-                temp = gr.Slider(label = "Temperature", value=1.0, minimum=0.1, maximum=100.0)
-                repetition_penalty = gr.Slider(label = "Repetition Penalty", minimum=0.0, value=3.0, step=0.1)
-                num_beams = gr.Slider(label = "Number of beams", minimum=1,
-                    		maximum=10, value=3)
-                do_sample = gr.Radio(choices = [True, False], value = True, label = "Sampling")
-                generation_params = [max_new_tokens, length_penalty,
-                                    top_k, top_p, temp, num_beams,
-                                    do_sample]
-            with gr.Row():
+                with gr.Column():
+                    max_new_tokens = gr.Slider(label = "Maximum length",
+                    		minimum = 0,
+                    		maximum = 512,
+                    		value = 128)
+                    length_penalty = gr.Slider(label = "Length penalty",
+                        		value=1.0)
+                    top_k = gr.Slider(label = "Top-k", value=10)
+                    top_p = gr.Slider(label = "Top-p", value=0.95)
+                    temp = gr.Slider(label = "Temperature", value=1.0, minimum=0.1, maximum=100.0)
+                    repetition_penalty = gr.Slider(label = "Repetition Penalty", minimum=0.0, value=3.0, step=0.1)
+                    num_beams = gr.Slider(label = "Number of beams", minimum=1,
+                        		maximum=10, value=3)
+                    do_sample = gr.Radio(choices = [True, False], value = True, label = "Sampling")
                 
                 text_gen_input = gr.Textbox(label="Text Generation Input")
             
                 text_gen_submit = gr.Button()
                 text_gen_output = gr.Textbox(label="Text Generation Output")
-                text_gen_submit.click(turna, inputs=[text_gen_input, generation_params], outputs=text_gen_output)
+                text_gen_submit.click(turna, inputs=[text_gen_input, max_new_tokens, length_penalty,
+                                    top_k, top_p, temperature=temp, num_beams,
+                                    do_sample], outputs=text_gen_output)
             text_gen_example = [["Bir varmış, bir yokmuş, evvel zaman içinde, kalbur saman içinde, uzak diyarların birinde bir turna"]]
-            text_gen_examples = gr.Examples(examples = text_gen_example, inputs = [text_gen_input, generation_params], outputs=text_gen_output, fn=turna)
+            text_gen_examples = gr.Examples(examples = text_gen_example, inputs = [text_gen_input, max_new_tokens, length_penalty,
+                                    top_k, top_p, temp, num_beams, do_sample], outputs=text_gen_output, fn=turna)
         
     with gr.Tab("Text Categorization"):
         gr.Markdown("TURNA fine-tuned on text categorization. Enter text to categorize text or try the example.")
@@ -163,12 +163,8 @@ with gr.Blocks(theme="abidlabs/Lime") as demo:
                 
                     text_submit = gr.Button()
                 text_output = gr.Textbox(label="Text Categorization Output")
-                text_submit.click(categorize, inputs=[text_input, max_new_tokens, length_penalty,
-                                    top_k, top_p, temp, num_beams,
-                                    do_sample], outputs=text_output)
-            text_examples = gr.Examples(examples = text_category_example, inputs = [text_input, max_new_tokens, length_penalty,
-                                    top_k, top_p, temp, num_beams,
-                                    do_sample], outputs=text_output, fn=categorize)
+                text_submit.click(categorize, inputs=[text_input], outputs=text_output)
+            text_examples = gr.Examples(examples = text_category_example, fn=categorize)
         
     
     with gr.Tab("NLI"):