Update app.py

app.py

@@ -1,11 +1,21 @@
-from transformers import pipeline, set_seed
+from transformers import AutoModelWithLMHead, AutoTokenizer
 import gradio as grad
-gpt2_pipe = pipeline('text-generation', model='distilgpt2')
-set_seed(42)
 
-def generate(starting_text):
-    response= gpt2_pipe(starting_text, max_length=20, num_return_sequences=5)
+text2text_tkn = AutoTokenizer.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
+mdl = AutoModelWithLMHead.from_pretrained("mrm8488/t5-base-finetuned-question-generation-ap")
+
+def text2text(context,answer):
+    input_text = "answer: %s  context: %s </s>" % (answer, context)
+    features = text2text_tkn ([input_text], return_tensors='pt')
+
+    output = mdl.generate(input_ids=features['input_ids'], 
+               attention_mask=features['attention_mask'],
+               max_length=64)
+
+    response=text2text_tkn.decode(output[0])    
     return response
-txt=grad.Textbox(lines=1, label="English", placeholder="English Text here")
-out=grad.Textbox(lines=1, label="Generated Text")
-grad.Interface(generate, inputs=txt, outputs=out).launch()
+
+context=grad.Textbox(lines=10, label="English", placeholder="Context")
+ans=grad.Textbox(lines=1, label="Answer")
+out=grad.Textbox(lines=1, label="Genereated Question")
+grad.Interface(text2text, inputs=[context,ans], outputs=out).launch()