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import gradio as gr
from gradio.mix import Parallel
description = "Poem meter detector"
title = "Identify the meter of the poem you are reading or writing with this performant classifier"
examples = [["ุณูŽู„ูˆ ู‚ูŽู„ุจูŠ ุบูŽุฏุงุฉูŽ ุณูŽู„ุง ูˆูŽุซุงุจุง ู„ูŽุนูŽู„ูŽู‘ ุนูŽู„ู‰ ุงู„ุฌูŽู…ุงู„ู ู„ูŽู‡ู ุนูุชุงุจุง"], ["ู‚ูุง ู†ุจูƒ ู…ู† ุฐููƒุฑู‰ ุญุจูŠุจ ูˆู…ู†ุฒู„ู ุจุณูู‚ุทู ุงู„ู„ูู‘ูˆู‰ ุจูŠู†ูŽ ุงู„ุฏูŽู‘ุฎูˆู„ ูุญูŽูˆู’ู…ู„ู"]]
meter = gr.Interface.load("huggingface/Yah216/Arabic_poem_meter_3",
description="Meter detector",
examples=examples
)
qafiyah = gr.Interface.load("huggingface/Yah216/Poem_Qafiyah_Detection",
description="Qafiyah",
examples=examples
)
subject = gr.Interface.load(
"huggingface/zenkri/autotrain-Arabic_Poetry_by_Subject-920730230",
description="Subject detector",
examples=examples
)
demo = gr.TabbedInterface([meter, qafiyah, subject], ["ุงู„ุชุนุฑู ุนู„ู‰ ุงู„ุจุญุฑ","ุงู„ุชุนุฑู ุนู„ู‰ ุงู„ู‚ุงููŠุฉ","ุงู„ุชุนุฑู ุนู„ู‰ ุงู„ู…ูˆุถูˆุน"])
demo.launch()
#Parallel(interface1, interface2, interface3, examples = examples).launch()