Update app.py

app.py

@@ -1,8 +1,13 @@
 from transformers import AutoModelWithLMHead, AutoTokenizer
 import gradio as grad
 
-text2text_tkn = AutoTokenizer.from_pretrained('mrm8488/t5-base-finetuned-question-generation-ap')
-mdl = AutoModelWithLMHead.from_pretrained('mrm8488/t5-base-finetuned-question-generation-ap')
+# make a question
+# text2text_tkn = AutoTokenizer.from_pretrained('mrm8488/t5-base-finetuned-question-generation-ap')
+# mdl = AutoModelWithLMHead.from_pretrained('mrm8488/t5-base-finetuned-question-generation-ap')
+
+# summarize
+text2text_tkn = AutoTokenizer.from_pretrained('deep-learning-analytics/wikihow-t5-small')
+mdl = AutoModelWithLMHead.from_pretrained('deep-learning-analytics/wikihow-t5-small')
 
 def text2text(context, answer):
     input_text = "answer: %s context: %s </s>" % (answer, context)
@@ -16,11 +21,32 @@ def text2text(context, answer):
 
     return response
 
-context = grad.Textbox(lines = 10, label = 'English', placeholder = 'Context')
-ans = grad.Textbox(lines = 1, label = 'Answer')
-out = grad.Textbox(lines = 1, label = 'Generated Question')
+def text2text_summary(para):
+    initial_txt = para.strip().replace("\n", "")
+    tkn_text = text2text_tkn.encode(initial_txt, return_tensors = 'pt')
+    tkn_ids = mdl.generate(
+        tkn_text,
+        max_length = 250,
+        num_beams = 5,
+        repetition_penalty = 2.5,
+        early_stopping = True
+    )
+
+    response = text2text_tkn.encode(tkn_ids[0], skip_special_tokens = True)
+
+    return response
+
+# context = grad.Textbox(lines = 10, label = 'English', placeholder = 'Context')
+# ans = grad.Textbox(lines = 1, label = 'Answer')
+# out = grad.Textbox(lines = 1, label = 'Generated Question')
+
+para = grad.Textbox(lines = 10, label = 'Paragraph', placeholder = 'Copy paragraph')
+out = grad.Textbox(lines = 1, label = 'Summary')
+
 grad.Interface(
-    text2text,
-    inputs = [context, ans],
+   # text2text,
+    # inputs = [context, ans],
+    text2text_summary,
+    inputs = para,
     outputs = out
 ).launch()