Spaces:
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CPU Upgrade
Running
on
CPU Upgrade
update ui
Browse filesno idea why it doesnt work
app.py
CHANGED
@@ -507,7 +507,7 @@ if __name__ == "__main__":
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"""
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)
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with gr.Row(variant="compact"):
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with gr.Column(
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model_name = gr.Dropdown(
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choices=MODEL_OPTIONS,
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value=MODEL_OPTIONS[0],
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@@ -537,7 +537,7 @@ if __name__ == "__main__":
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with gr.Row():
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input_text = gr.Textbox(
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lines=4,
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max_lines=
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label="Text to Summarize",
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placeholder="Enter text to summarize, the text will be cleaned and truncated on Spaces. Narrative, academic (both papers and lecture transcription), and article text work well. May take a bit to generate depending on the input text :)",
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)
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@@ -643,18 +643,6 @@ if __name__ == "__main__":
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label="Drop Stopwords (Pre-Truncation)",
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value=False,
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)
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with gr.Column():
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gr.Markdown("## About")
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gr.Markdown(
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"- Models are fine-tuned on the [🅱️ookSum dataset](https://arxiv.org/abs/2105.08209). The goal was to create a model that generalizes well and is useful for summarizing text in academic and everyday use."
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gr.Markdown(
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"- _Update April 2023:_ Additional models fine-tuned on the [PLOS](https://hf.co/datasets/pszemraj/scientific_lay_summarisation-plos-norm) and [ELIFE](https://hf.co/datasets/pszemraj/scientific_lay_summarisation-elife-norm) subsets of the [scientific lay summaries](https://arxiv.org/abs/2210.09932) dataset are available (see dropdown at the top)."
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gr.Markdown(
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"Adjust the max input words & max PDF pages for OCR by duplicating this space and [setting the environment variables](https://hf.co/docs/hub/spaces-overview#managing-secrets) `APP_MAX_WORDS` and `APP_OCR_MAX_PAGES` to the desired integer values."
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)
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gr.Markdown("---")
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load_examples_button.click(
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fn=load_single_example_text, inputs=[example_name], outputs=[input_text]
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"""
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)
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with gr.Row(variant="compact"):
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with gr.Column(variant="compact"):
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model_name = gr.Dropdown(
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choices=MODEL_OPTIONS,
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value=MODEL_OPTIONS[0],
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with gr.Row():
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input_text = gr.Textbox(
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lines=4,
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max_lines=8,
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label="Text to Summarize",
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placeholder="Enter text to summarize, the text will be cleaned and truncated on Spaces. Narrative, academic (both papers and lecture transcription), and article text work well. May take a bit to generate depending on the input text :)",
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)
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label="Drop Stopwords (Pre-Truncation)",
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value=False,
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)
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load_examples_button.click(
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fn=load_single_example_text, inputs=[example_name], outputs=[input_text]
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