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"""Copy of [Student]_Module_2_Session_3.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/13eYUvAlEmfXWn-v_fMXgvmvqXJTPq7ys |
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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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pipe = pipeline("text-classification", model="finiteautomata/bertweet-base-sentiment-analysis") |
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"""Import the pipeline :""" |
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sentiment = pipe("I really enjoyed my stay !") |
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print(sentiment) |
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"""Test the pipeline on these reviews (you can also test on your own reviews) :""" |
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sentiment = pipe("Worst rental I ever got") |
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print(sentiment) |
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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(pipe("Worst rental I ever got")[0]["label"]) |
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print(pipe("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 pipe(text)[0]["label"], pipe(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,inputs=gr.Textbox(lines=2, label="Enter Review:"), |
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outputs=[gr.Text(label="Setiment:"),gr.Text(label="Score")]) |
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interface.launch() |
