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Upload sentiment_analysis.py
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sentiment_analysis.py
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# -*- coding: utf-8 -*-
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"""Sentiment-analysis.ipynb
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Automatically generated by Colab.
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Original file is located at
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https://colab.research.google.com/drive/1pmME28f5Z7SNxUoX5va3W-90XP5zPnQu
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Installations
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"""
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!pip install gradio --quiet
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!pip install transformers --quiet
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"""#Let's build a demo for a sentiment analysis task !
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Import the necessary modules :
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"""
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from transformers import pipeline
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import gradio as gr
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"""Import the pipeline :"""
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sentiment = pipeline("sentiment-analysis")
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"""Test the pipeline on these reviews (you can also test on your own reviews) :"""
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#"I really enjoyed my stay !"
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#"Worst rental I ever got"
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sentiment("I really enjoyed my stay !")
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"""What is the format of the output ? How can you get only the sentiment or the confidence score ?"""
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print(sentiment("I really enjoyed my stay !")[0]['label'])
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print(sentiment("I really enjoyed my stay !")[0]['score'])
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print(sentiment("Worst rental I ever got")[0]['label'])
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print(sentiment("Worst rental I ever got")[0]['score'])
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"""Create a function that takes a text in input, and returns a sentiment, and a confidence score as 2 different variables"""
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def get_sentiment(text):
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return sentiment(text)[0]['label'], sentiment(text)[0]['score']
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"""Build an interface for the app using Gradio.
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The customer wants this result :
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"""
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interface = gr.Interface(fn=get_sentiment,
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inputs=gr.Textbox(lines=1, label="Enter the review:"),
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outputs=[gr.Text(label='Sentiment:'),
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gr.Text(label='Score:')])
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interface.launch()
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ar_sentiment = pipeline("sentiment-analysis", model='CAMeL-Lab/bert-base-arabic-camelbert-da-sentiment')
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ar_sentiment('انا احب ذلك')
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def get_ar_sentiment(text):
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return ar_sentiment(text)[0]['label'], ar_sentiment(text)[0]['score']
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interface = gr.Interface(fn=get_ar_sentiment,
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inputs=gr.Textbox(lines=1, label="Enter the review:"),
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outputs=[gr.Text(label='Sentiment:'),
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gr.Text(label='Score:')])
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interface.launch()
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