Spaces:
Running
on
Zero
Running
on
Zero
da03
commited on
Commit
·
ee2ee31
1
Parent(s):
8e09eb8
app.py
CHANGED
@@ -141,7 +141,7 @@ demo = gr.Interface(
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gr.HighlightedText(label='No CoT Predicted Product', combine_adjacent=False, show_legend=False, color_map=color_map, show_inline_category=False),
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gr.HighlightedText(label='Explicit CoT Predicted Product', combine_adjacent=False, show_legend=False, color_map=color_map, show_inline_category=False),
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],
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title='Use GPT2 to
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description='This demo shows it\'s possible to use GPT2 to directly predict the product of two large numbers without using any intermediate reasoning steps. The GPT2 model has been finetuned to internalize chain-of-thought (CoT) reasoning within its hidden states, following our stepwise internalization approach detailed in the paper linked at the bottom of this page.',
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article="""
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- [Paper: From Explicit CoT to Implicit CoT: Learning to Internalize CoT Step by Step](https://arxiv.org/pdf/2405.14838)
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gr.HighlightedText(label='No CoT Predicted Product', combine_adjacent=False, show_legend=False, color_map=color_map, show_inline_category=False),
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gr.HighlightedText(label='Explicit CoT Predicted Product', combine_adjacent=False, show_legend=False, color_map=color_map, show_inline_category=False),
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],
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+
title='Use GPT2 to Predict Multiplication of Two Numbers (Without Using Intermediate Steps)',
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description='This demo shows it\'s possible to use GPT2 to directly predict the product of two large numbers without using any intermediate reasoning steps. The GPT2 model has been finetuned to internalize chain-of-thought (CoT) reasoning within its hidden states, following our stepwise internalization approach detailed in the paper linked at the bottom of this page.',
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article="""
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- [Paper: From Explicit CoT to Implicit CoT: Learning to Internalize CoT Step by Step](https://arxiv.org/pdf/2405.14838)
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