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!pip install gradio | |
!pip install transformers | |
import gradio as gr | |
from transformers import pipeline | |
def aspects(sentense): | |
sentense=[sentense] | |
sentimentdata=sentiment(sentense) | |
fit_score=process.default_scorer(sentense,fit) | |
mat_score=process.default_scorer(sentense,material) | |
price_score=process.default_scorer(sentense,price) | |
sentimentlabel=sentimentdata[0].get("label") | |
sentprobability=sentimentdata[0].get("score") | |
return sentimentlabel,sentprobability,fit_score,price_score,mat_score | |
pipe = pipeline("sentiment-analysis") | |
interface=gr.Interface(fn=aspects,inputs=gr.inputs.Textbox(lines=10,placeholder="please insert your text"), | |
examples=[ | |
["this product and not fitting well to my body and feel scratchy"], | |
["this fabric is super cool and feel very comfortable "] | |
], | |
title="Review Analyzer", | |
outputs=[gr.outputs.Textbox(type="auto", label="Sentiment"), | |
gr.outputs.Textbox(type="auto", label="Sentiment score"), | |
gr.outputs.Textbox(type="auto", label="Fit related score"), | |
gr.outputs.Textbox(type="auto", label="Price related score"), | |
gr.outputs.Textbox(type="auto", label="Material related score")],live=True) | |
interface.launch() |