Update

app.py

@@ -1,7 +1,29 @@
-import gradio as gr
+import torch
+from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
+model = AutoModelForSeq2SeqLM.from_pretrained("Mihakram/AraT5-base-question-generation")
+tokenizer = AutoTokenizer.from_pretrained("Mihakram/AraT5-base-question-generation")  
+
 
-def greet(name):
-    return "Hello " + name + "!!"
+import gradio as gr
+def generate__questions(context,answer):
+  text="context: " +context + " " + "answer: " + answer + " </s>"
+  text_encoding = tokenizer.encode_plus(
+      text,return_tensors="pt"
+  )
+  model.eval()
+  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
+  )
+  
+  return tokenizer.decode(generated_ids[0],skip_special_tokens=True,clean_up_tokenization_spaces=True).replace('question: ',' ')
 
-iface = gr.Interface(fn=greet, inputs="text", outputs="text")
-iface.launch()
+demo = gr.Interface(fn=generate__questions, inputs=[gr.Textbox(label='Context'),
+                                                    gr.Textbox(label='Answer')] ,
+                                                    outputs=gr.Textbox(label='Question'),
+                                                    title="Arabic Question Generation",
+                                                    description="Get the Question from given Context and an Answer")
+demo.launch()    

requirements.txt

@@ -0,0 +1,2 @@
+torch
+transformers