saritha5 commited on
Commit
0a93cce
1 Parent(s): 5e41c07

Update app.py

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Files changed (1) hide show
  1. app.py +1 -12
app.py CHANGED
@@ -46,17 +46,7 @@ def prediction(text):
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  sum_len = len(summary.split(' '))
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  return summary,org_len,sum_len
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- text = """
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- Maria Sharapova has basically no friends as tennis players on the WTA Tour. The Russian player has no problems in openly speaking about it and in a recent interview she said: 'I don't really hide any feelings too much.
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- I think everyone knows this is my job here. When I'm on the courts or when I'm on the court playing, I'm a competitor and I want to beat every single person whether they're in the locker room or across the net.
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- So I'm not the one to strike up a conversation about the weather and know that in the next few minutes I have to go and try to win a tennis match.
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- I'm a pretty competitive girl. I say my hellos, but I'm not sending any players flowers as well. Uhm, I'm not really friendly or close to many players.
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- I have not a lot of friends away from the courts.' When she said she is not really close to a lot of players, is that something strategic that she is doing? Is it different on the men's tour than the women's tour? 'No, not at all.
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- I think just because you're in the same sport doesn't mean that you have to be friends with everyone just because you're categorized, you're a tennis player, so you're going to get along with tennis players.
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- I think every person has different interests. I have friends that have completely different jobs and interests, and I've met them in very different parts of my life.
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- I think everyone just thinks because we're tennis players we should be the greatest of friends. But ultimately tennis is just a very small part of what we do.
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- There are so many other things that we're interested in, that we do.'
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- """
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  #predicted_label, score = occ_predict("img1.jpg")
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  #inputs = gr.inputs.text(label)
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  #label = gr.outputs.Label(num_top_classes=2)
@@ -76,7 +66,6 @@ demo_app = gr.Interface(
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  outputs= outputs,
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  title = "Text Summarization",
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  #description = DESCRIPTION,
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- examples = text,
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  #cache_example = True,
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  #live = True,
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  theme = 'huggingface'
 
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  sum_len = len(summary.split(' '))
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  return summary,org_len,sum_len
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+
 
 
 
 
 
 
 
 
 
 
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  #predicted_label, score = occ_predict("img1.jpg")
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  #inputs = gr.inputs.text(label)
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  #label = gr.outputs.Label(num_top_classes=2)
 
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  outputs= outputs,
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  title = "Text Summarization",
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  #description = DESCRIPTION,
 
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  #cache_example = True,
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  #live = True,
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  theme = 'huggingface'