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Runtime error
MeetJivani
commited on
Commit
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cb217fc
1
Parent(s):
990b5e2
Update app.py
Browse files
app.py
CHANGED
@@ -312,7 +312,7 @@ def proc_submission(
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settings["remove_stopwords"] = predrop_stopwords
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settings["model_name"] = model_name
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saved_file = saves_summary(summarize_output=_summaries, outpath=None, **settings)
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return html, full_summary, saved_file
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def load_single_example_text(
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@@ -571,14 +571,14 @@ if __name__ == "__main__":
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type="file",
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interactive=False,
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)
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with gr.Column(variant="panel"):
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gr.Markdown("### **Summary Output**")
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summary_text = gr.HTML(
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@@ -611,19 +611,19 @@ if __name__ == "__main__":
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# )
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gr.Markdown("---")
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# token_batch_length = gr.Radio(
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# choices=TOKEN_BATCH_OPTIONS,
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# label="token batch length",
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@@ -673,9 +673,10 @@ if __name__ == "__main__":
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fn=proc_submission,
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inputs=[
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input_text,
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model_name
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],
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outputs=[output_text, summary_text, text_file],
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)
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# aggregate_button.click(
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# fn=aggregate_text,
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settings["remove_stopwords"] = predrop_stopwords
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settings["model_name"] = model_name
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saved_file = saves_summary(summarize_output=_summaries, outpath=None, **settings)
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return html, full_summary,scores_out, saved_file
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def load_single_example_text(
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type="file",
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interactive=False,
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)
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with gr.Column(variant="compact"):
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gr.Markdown(
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"Scores **roughly** represent the summary quality as a measure of the model's 'confidence'. less-negative numbers (closer to 0) are better."
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)
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summary_scores = gr.Textbox(
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label="Summary Scores",
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placeholder="Summary scores will appear here",
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)
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with gr.Column(variant="panel"):
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gr.Markdown("### **Summary Output**")
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summary_text = gr.HTML(
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# )
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gr.Markdown("---")
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with gr.Column():
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gr.Markdown("### Advanced Settings")
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# gr.Markdown(
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# "Refer to [the guide doc](https://gist.github.com/pszemraj/722a7ba443aa3a671b02d87038375519) for what these are, and how they impact _quality_ and _speed_."
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# )
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with gr.Row(variant="compact"):
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length_penalty = gr.Slider(
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minimum=0.3,
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maximum=1.1,
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label="length penalty",
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value=0.7,
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step=0.05,
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)
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# token_batch_length = gr.Radio(
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# choices=TOKEN_BATCH_OPTIONS,
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# label="token batch length",
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fn=proc_submission,
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inputs=[
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input_text,
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model_name,
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length_penalty
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],
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outputs=[output_text, summary_text,summary_scores, text_file],
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)
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# aggregate_button.click(
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# fn=aggregate_text,
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