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Runtime error
Update app.py
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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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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)
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@@ -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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#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'
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