TrungNQ commited on
Commit
ea5770c
·
verified ·
1 Parent(s): ce4a251

Update app.py

Browse files
Files changed (1) hide show
  1. app.py +29 -1
app.py CHANGED
@@ -69,7 +69,7 @@ out=grad.Textbox(lines=1, label="Generated Tensors")
69
  grad.Interface(generate, inputs=txt, outputs=out).launch()
70
  '''
71
 
72
- #5.20
73
  from transformers import AutoModelWithLMHead, AutoTokenizer
74
  import gradio as grad
75
 
@@ -91,3 +91,31 @@ context=grad.Textbox(lines=10, label="English", placeholder="Context")
91
  ans=grad.Textbox(lines=1, label="Answer")
92
  out=grad.Textbox(lines=1, label="Genereated Question")
93
  grad.Interface(text2text, inputs=[context,ans], outputs=out).launch()
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
69
  grad.Interface(generate, inputs=txt, outputs=out).launch()
70
  '''
71
 
72
+ '''5.20
73
  from transformers import AutoModelWithLMHead, AutoTokenizer
74
  import gradio as grad
75
 
 
91
  ans=grad.Textbox(lines=1, label="Answer")
92
  out=grad.Textbox(lines=1, label="Genereated Question")
93
  grad.Interface(text2text, inputs=[context,ans], outputs=out).launch()
94
+ '''
95
+
96
+ #5.21
97
+ from transformers import AutoTokenizer, AutoModelWithLMHead
98
+ import gradio as grad
99
+ text2text_tkn = AutoTokenizer.from_pretrained("deep-learning-analytics/wikihow-t5-small")
100
+ mdl = AutoModelWithLMHead.from_pretrained("deep-learning-analytics/wikihow-t5-small")
101
+
102
+
103
+ def text2text_summary(para):
104
+ initial_txt = para.strip().replace("\n","")
105
+ tkn_text = text2text_tkn.encode(initial_txt, return_tensors="pt")
106
+
107
+ tkn_ids = mdl.generate(
108
+ tkn_text,
109
+ max_length=250,
110
+ num_beams=5,
111
+ repetition_penalty=2.5,
112
+
113
+ early_stopping=True
114
+ )
115
+
116
+ response = text2text_tkn.decode(tkn_ids[0], skip_special_tokens=True)
117
+ return response
118
+
119
+ para=grad.Textbox(lines=10, label="Paragraph", placeholder="Copy paragraph")
120
+ out=grad.Textbox(lines=1, label="Summary")
121
+ grad.Interface(text2text_summary, inputs=para, outputs=out).launch()