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abhishek1992
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4a4cf55
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Parent(s):
55efd67
Update app.py
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app.py
CHANGED
@@ -4,7 +4,7 @@ from transformers import pipeline
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pipe = pipeline("question-answering", model="deepset/roberta-large-squad2")
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def
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context = '''Sun Ultra hardware and Solaris operating system technology are used to support all client server modules including human machine interface (HMI) and application clients. HMI client modules are also available on Intel systems running the Microsoft Windows operating system.
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The operational environment gives a common look and feel on all operating systems, combined with an “operate from anywhere” network connectivity to the SCADA database.
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SCADA system components are arranged redundantly to support very high availability platforms. Redundant components may include:Human Machine Interface (HMI),Front-End Processor (FEP),Database,Calculations,History,Communications,Networks and workstations.
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@@ -50,7 +50,7 @@ A SCADA process monitor runs in each UNIX workstation to supervise and report on
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answer = pipe(question=input_text, context=context)
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return answer
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iface = gr.Interface(fn =
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inputs = "text",
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outputs = ['text'],
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title = 'question-answering',
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pipe = pipeline("question-answering", model="deepset/roberta-large-squad2")
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def get_answer(input_text):
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context = '''Sun Ultra hardware and Solaris operating system technology are used to support all client server modules including human machine interface (HMI) and application clients. HMI client modules are also available on Intel systems running the Microsoft Windows operating system.
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The operational environment gives a common look and feel on all operating systems, combined with an “operate from anywhere” network connectivity to the SCADA database.
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SCADA system components are arranged redundantly to support very high availability platforms. Redundant components may include:Human Machine Interface (HMI),Front-End Processor (FEP),Database,Calculations,History,Communications,Networks and workstations.
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answer = pipe(question=input_text, context=context)
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return answer
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iface = gr.Interface(fn = get_answer,
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inputs = "text",
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outputs = ['text'],
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title = 'question-answering',
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