liujch1998 commited on
Commit
a1f4642
·
1 Parent(s): 94a59f6
Files changed (1) hide show
  1. app.py +9 -9
app.py CHANGED
@@ -123,18 +123,18 @@ examples = [
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  'Causes bad breath and frightens blood-suckers \\n (A) tuna (B) iron (C) trash (D) garlic (E) pubs',
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  ]
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- input_question = gr.inputs.Dropdown(
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  choices=examples,
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  label='Question:',
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- # info='A multiple-choice commonsense question. Please follow the UnifiedQA input format: "{question} \\n (A) ... (B) ... (C) ..."',
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  )
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- input_kg_model = gr.inputs.Textbox(label='Knowledge generation model:', value='liujch1998/rainier-large', interactive=False)
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- input_qa_model = gr.inputs.Textbox(label='QA model:', value='allenai/unifiedqa-t5-large', interactive=False)
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- input_max_input_len = gr.inputs.Number(label='Max question length:', value=256, precision=0)
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- input_max_output_len = gr.inputs.Number(label='Max knowledge length:', value=32, precision=0)
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- input_m = gr.inputs.Slider(label='Number of generated knowledges:', value=10, mininum=1, maximum=20, step=1)
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- input_top_p = gr.inputs.Slider(label='Top_p for knowledge generation:', value=0.5, mininum=0.0, maximum=1.0, step=0.05)
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- output_text = gr.outputs.Textbox(label='Output')
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  gr.Interface(
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  fn=predict,
 
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  'Causes bad breath and frightens blood-suckers \\n (A) tuna (B) iron (C) trash (D) garlic (E) pubs',
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  ]
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+ input_question = gr.Dropdown(
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  choices=examples,
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  label='Question:',
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+ info='A multiple-choice commonsense question. Please follow the UnifiedQA input format: "{question} \\n (A) ... (B) ... (C) ..."',
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  )
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+ input_kg_model = gr.Textbox(label='Knowledge generation model:', value='liujch1998/rainier-large', interactive=False)
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+ input_qa_model = gr.Textbox(label='QA model:', value='allenai/unifiedqa-t5-large', interactive=False)
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+ input_max_input_len = gr.Number(label='Max question length:', value=256, precision=0)
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+ input_max_output_len = gr.Number(label='Max knowledge length:', value=32, precision=0)
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+ input_m = gr.Slider(label='Number of generated knowledges:', value=10, mininum=1, maximum=20, step=1)
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+ input_top_p = gr.Slider(label='Top_p for knowledge generation:', value=0.5, mininum=0.0, maximum=1.0, step=0.05)
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+ output_text = gr.Textbox(label='Output', interactive=False)
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  gr.Interface(
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  fn=predict,