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Peter
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app.py
CHANGED
@@ -101,14 +101,7 @@ if __name__ == "__main__":
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model, tokenizer = load_model_and_tokenizer("pszemraj/led-large-book-summary")
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model_sm, tokenizer_sm = load_model_and_tokenizer("pszemraj/led-base-book-summary")
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title = "Long-Form Summarization: LED & BookSum"
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description = "
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- [This model](https://huggingface.co/pszemraj/led-large-book-summary) is a fine-tuned version of [allenai/led-large-16384](https://huggingface.co/allenai/led-large-16384) on the [BookSum dataset](https://arxiv.org/abs/2105.08209).
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- The goal was to create a model that can generalize well and is useful in summarizing lots of text in academic and daily usage.
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- See [model card](https://huggingface.co/pszemraj/led-large-book-summary) for a notebook with GPU inference (much faster) on Colab.
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"""
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gr.Interface(
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proc_submission,
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inputs=[
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model, tokenizer = load_model_and_tokenizer("pszemraj/led-large-book-summary")
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model_sm, tokenizer_sm = load_model_and_tokenizer("pszemraj/led-base-book-summary")
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title = "Long-Form Summarization: LED & BookSum"
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description = "A simple demo of how to use a fine-tuned LED model to summarize long-form text. [This model](https://huggingface.co/pszemraj/led-large-book-summary) is a fine-tuned version of [allenai/led-large-16384](https://huggingface.co/allenai/led-large-16384) on the [BookSum dataset](https://arxiv.org/abs/2105.08209).The goal was to create a model that can generalize well and is useful in summarizing lots of text in academic and daily usage. See [model card](https://huggingface.co/pszemraj/led-large-book-summary) for a notebook with GPU inference (much faster) on Colab."
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gr.Interface(
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proc_submission,
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inputs=[
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