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