Update

app.py

@@ -1,12 +1,20 @@
 import torch
 from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
-model_name = "Tahsin-Mayeesha/squad-bn-mt5-base2"
-model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
-tokenizer = AutoTokenizer.from_pretrained(model_name)  
+import gradio as gr
 
+def choose_model(model_choice):
+  if model_choice=="mt5-small":
+    return "jannatul17/squad-bn-qgen-mt5-small-v1"
+  elif model_choice=="mt5-base":
+    return "Tahsin-Mayeesha/squad-bn-mt5-base2"
+  else :
+    return "jannatul17/squad-bn-qgen-banglat5-v1"
 
-import gradio as gr
-def generate__questions(context,answer):
+
+def generate__questions(model_choice,context,answer):
+  model_name = choose_model(model_choice)
+  model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
+  tokenizer = AutoTokenizer.from_pretrained(model_name)  
   text='answer: '+answer + ' context: ' + context
   text_encoding = tokenizer.encode_plus(
       text,return_tensors="pt"
@@ -22,7 +30,8 @@ def generate__questions(context,answer):
   
   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.Textbox(label='Context'),
+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')] ,
                                                     outputs=gr.Textbox(label='Question'),
                                                     title="Bangla Question Generation",