romanbredehoft-zama
commited on
Commit
·
e3103dd
1
Parent(s):
cb3c1a3
Improving some wording
Browse files- app.py +8 -9
- backend.py +1 -1
app.py
CHANGED
@@ -63,21 +63,20 @@ with demo:
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gr.Markdown("## Step 2: Fill in some information.")
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gr.Markdown(
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"""
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-
Select
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-
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-
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provide any information relevant to the decision
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"""
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)
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with gr.Row():
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with gr.Column():
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gr.Markdown("### User")
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-
bool_inputs = gr.CheckboxGroup(["Car", "Property", "Work phone", "Phone", "Email"], label="
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num_children = gr.Slider(**CHILDREN_MIN_MAX, step=1, label="Number of children", info="How many children do you have ?")
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household_size = gr.Slider(**FAMILY_MIN_MAX, step=1, label="Household size", info="How many members does your household have? ?")
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total_income = gr.Slider(**INCOME_MIN_MAX, label="Income", info="What's you total yearly income (in euros) ?")
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gr.Markdown("## Step 2: Fill in some information.")
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gr.Markdown(
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"""
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+
Select the information that corresponds to the profile you want to evaluate. Three sources
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of information are represented in this model:
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- a user's personal information in order to evaluate his/her credit card eligibility;
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- the user’s bank account history, which provides any type of information on the user's
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banking information relevant to the decision (here, we consider duration of account);
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- and third party information, which represents any other information (here, employment
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history) that could provide additional insight relevant to the decision.
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"""
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)
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with gr.Row():
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with gr.Column():
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gr.Markdown("### User")
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bool_inputs = gr.CheckboxGroup(["Car", "Property", "Work phone", "Phone", "Email"], label="Which of the following do you actively hold or own?")
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num_children = gr.Slider(**CHILDREN_MIN_MAX, step=1, label="Number of children", info="How many children do you have ?")
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household_size = gr.Slider(**FAMILY_MIN_MAX, step=1, label="Household size", info="How many members does your household have? ?")
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total_income = gr.Slider(**INCOME_MIN_MAX, label="Income", info="What's you total yearly income (in euros) ?")
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backend.py
CHANGED
@@ -422,4 +422,4 @@ def decrypt_output(client_id):
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output = numpy.argmax(output_proba, axis=1).squeeze()
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# A "0" output means approving the credit card has low risk, while "1" is high risk
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return "Credit card
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output = numpy.argmax(output_proba, axis=1).squeeze()
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# A "0" output means approving the credit card has low risk, while "1" is high risk
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return "Credit card is likely to be approved ✅" if output == 0 else "Credit card is likely to be denied ❌"
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