umm-maybe commited on
Commit
ee7bc16
1 Parent(s): 24cc048

Add description and contact information

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Files changed (1) hide show
  1. app.py +2 -3
app.py CHANGED
@@ -69,14 +69,13 @@ def getTour(income,size,years,sex,edu,wrk):
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  return activity_list
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  with gr.Interface(fn=getTour, inputs=[
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- gr.Markdown("## Activity Sequence Modeling Using Transformers"),
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  gr.Markdown("This demo uses a GPT-2 model fine-tuned on activity sequences from the 2017 National Household Travel Survey (NHTS) to generate activity sequences for a given person. The model is trained to predict the next activity in a sequence given the previous activities, and is conditioned on person-level and household-level attributes."),
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- gr.Markdown("# For more information, contact: colby@manhangroup.com"),
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  gr.Textbox(label="Annual Household Income (in dollars)"),
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  gr.Textbox(label="Household Size (number of people)"),
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  gr.Textbox(label="Traveler Age (years)"),
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  gr.Dropdown(["unknown", "male", "female"], label="Gender/sex"),
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  gr.Dropdown(["unknown", "grade school","highschool", "associates", "bachelors", "graduate"], label="Educational attainment level"),
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  gr.Dropdown(["unknown", "yes","no"], label="Worker status")],
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- outputs=["json"], title="GPT-Travel", description="Activity Sequence Modeling Using Transformers", allow_flagging='never') as iface:
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  iface.launch()
 
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  return activity_list
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  with gr.Interface(fn=getTour, inputs=[
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+ gr.Markdown("# Activity Sequence Modeling Using Transformers"),
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  gr.Markdown("This demo uses a GPT-2 model fine-tuned on activity sequences from the 2017 National Household Travel Survey (NHTS) to generate activity sequences for a given person. The model is trained to predict the next activity in a sequence given the previous activities, and is conditioned on person-level and household-level attributes."),
 
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  gr.Textbox(label="Annual Household Income (in dollars)"),
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  gr.Textbox(label="Household Size (number of people)"),
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  gr.Textbox(label="Traveler Age (years)"),
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  gr.Dropdown(["unknown", "male", "female"], label="Gender/sex"),
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  gr.Dropdown(["unknown", "grade school","highschool", "associates", "bachelors", "graduate"], label="Educational attainment level"),
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  gr.Dropdown(["unknown", "yes","no"], label="Worker status")],
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+ outputs=["json"], title="GPT-Travel", description="Author: Colby Brown, Manhan (colby@manhangroup.com)", allow_flagging='never') as iface:
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  iface.launch()