Update

app.py

@@ -14,7 +14,7 @@ def choose_model(model_choice):
     return "jannatul17/squad-bn-qgen-banglat5-v1"
 
 
-def generate__questions(model_choice,context,answer):
+def generate_questions(model_choice,context,answer,numReturnSequences=1,num_beams=None,do_sample=False,top_p=None,top_k=None,temperature=None):
   model_name = choose_model(model_choice)
   model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
   tokenizer = AutoTokenizer.from_pretrained(model_name)  
@@ -26,19 +26,38 @@ def generate__questions(model_choice,context,answer):
   generated_ids =  model.generate(
     input_ids=text_encoding['input_ids'],
     attention_mask=text_encoding['attention_mask'],
-    max_length=64,
-    num_beams=5,
-    num_return_sequences=1
+    max_length=120,
+    num_beams=num_beams,
+    do_sample=do_sample,
+    top_k = top_k,
+    top_p = top_p,
+    temperature = temperature,
+    num_return_sequences=numReturnSequences
   )
   
-  return tokenizer.decode(generated_ids[0],skip_special_tokens=True,clean_up_tokenization_spaces=True).replace('question: ',' ')
-
-demo = gr.Interface(fn=generate__questions, inputs=[gr.Dropdown(label="Model", choices=["mt5-small","mt5-base","banglat5"],value="banglat5"),
+  text = []
+  for id in generated_ids:
+    text.append(tokenizer.decode(id,skip_special_tokens=True,clean_up_tokenization_spaces=True).replace('question: ',' '))
+  
+  return " ".join(text)
+  
+  
+demo = gr.Interface(fn=generate_questions, inputs=[gr.Dropdown(label="Model", choices=["mt5-small","mt5-base","banglat5"],value="banglat5"),
                                                     gr.Textbox(label='Context'),
-                                                    gr.Textbox(label='Answer')] ,
+                                                    gr.Textbox(label='Answer'),
+                                                    # hyperparameters
+                                                    gr.Slider(1, 3, 1, step=1, label="Num return Sequences"),
+                                                    # beam search
+                                                    gr.Slider(1, 10,value=None, step=1, label="Beam width"),
+                                                    # top-k/top-p
+                                                    gr.Checkbox(label="Do Random Sample",value=False),
+                                                    gr.Slider(0, 50, value=None, step=1, label="Top K"),
+                                                    gr.Slider(0, 1, value=None, label="Top P/Nucleus Sampling"),
+                                                    gr.Slider(0.01, 1, value=None, label="Temperature") ] ,
+                                                    # output
                                                     outputs=gr.Textbox(label='Question'),
                                                     examples=[["banglat5",example_context,example_answer]],
                                                     cache_examples=False,
                                                     title="Bangla Question Generation",
                                                     description="Get the Question from given Context and an Answer")
-demo.launch()    
+demo.launch()